# Pinecone Docs: Pinecone Database Reference > Official Pinecone documentation for the vector database, Assistant, inference APIs, SDKs, and building production search and AI applications. ## Reference - [Pinecone Database / Reference / 2026-07 (latest) (109 pages)](https://docs.pinecone.io/_llms/pinecone-database/reference/2026-07-latest.md): Documentation for Pinecone Database / Reference / 2026-07 (latest). - [Pinecone Database / Reference / 2026-04 (100 pages)](https://docs.pinecone.io/_llms/pinecone-database/reference/2026-04.md): Documentation for Pinecone Database / Reference / 2026-04. ### 2025-10 #### APIs - [API reference](https://docs.pinecone.io/reference/api/introduction.md): Pinecone API reference overview for Database, Inference, and Admin endpoints with supported SDKs including Python, Node.js, Java, and Go. - [Authentication](https://docs.pinecone.io/reference/api/authentication.md): Pinecone API authentication guide covering API key generation, SDK client setup, and HTTP header configuration for authorized requests. - [Pinecone API versioning](https://docs.pinecone.io/reference/api/versioning.md): Learn how Pinecone versions its APIs by release date, how long each stable version is supported, and how to set the X-Pinecone-Api-Version header. - [Errors](https://docs.pinecone.io/reference/api/errors.md): Look up the HTTP status codes the Pinecone API returns, what each 2xx success and 4xx or 5xx error means, and where to handle them in production. ##### Database limits - [Pinecone Database limits overview](https://docs.pinecone.io/reference/api/database-limits.md): Reference for Pinecone Database rate, object, operation, and identifier limits, plus known index and serverless limitations. - [Rate limits](https://docs.pinecone.io/reference/api/database-limits/rate-limits.md): Request-per-second, monthly usage, and model throughput limits for Pinecone Database serverless indexes, and the 429 errors returned when you exceed them. - [Object limits](https://docs.pinecone.io/reference/api/database-limits/object-limits.md): Limits on the number and size of Pinecone Database projects, indexes, namespaces, storage, backups, and collections, by plan. - [Operation limits](https://docs.pinecone.io/reference/api/database-limits/operation-limits.md): Fixed limits on Pinecone Database operations, including upsert, update, import, query, fetch, and delete batch sizes and metadata filter expressions. - [Identifier limits](https://docs.pinecone.io/reference/api/database-limits/identifier-limits.md): Maximum length and allowed characters for Pinecone identifiers, including organization, project, index, namespace, and record names. - [Known limitations](https://docs.pinecone.io/reference/api/known-limitations.md): Known limitations and feature restrictions for Pinecone indexes, including upsert consistency, metadata rules, and serverless caveats. #### Database ##### Indexes - [List indexes](https://docs.pinecone.io/reference/api/2025-10/control-plane/list_indexes.md): List all indexes in a project. - [Create an index](https://docs.pinecone.io/reference/api/2025-10/control-plane/create_index.md): Create a Pinecone index. This is where you specify the measure of similarity, the dimension of vectors to be stored in the index, which cloud provider you would like to deploy with, and more. For guidance and examples, see [Create an index](https://docs.pinecone.io/guides/index-data/create-an-ind… - [Create an index with integrated embedding](https://docs.pinecone.io/reference/api/2025-10/control-plane/create_for_model.md): Create an index with integrated embedding. With this type of index, you provide source text, and Pinecone uses a [hosted embedding model](https://docs.pinecone.io/guides/index-data/create-an-index#embedding-models) to convert the text automatically during [upsert](https://docs.pinecone.io/referenc… - [Describe an index](https://docs.pinecone.io/reference/api/2025-10/control-plane/describe_index.md): Get a description of an index. - [Delete an index](https://docs.pinecone.io/reference/api/2025-10/control-plane/delete_index.md): Delete an existing index. - [Configure an index](https://docs.pinecone.io/reference/api/2025-10/control-plane/configure_index.md): Configure an existing index. For guidance and examples, see [Manage indexes](https://docs.pinecone.io/guides/manage-data/manage-indexes). - [Get index stats](https://docs.pinecone.io/reference/api/2025-10/data-plane/describeindexstats.md): Return statistics about the contents of an index, including the vector count per namespace, the number of dimensions, and the index fullness. ##### Namespaces - [List namespaces](https://docs.pinecone.io/reference/api/2025-10/data-plane/listnamespaces.md): List all namespaces in a serverless index. - [Create a namespace](https://docs.pinecone.io/reference/api/2025-10/data-plane/createnamespace.md): Create a namespace in a serverless index. - [Describe a namespace](https://docs.pinecone.io/reference/api/2025-10/data-plane/describenamespace.md): Describe a namespace in a serverless index, including the total number of vectors in the namespace. - [Delete a namespace](https://docs.pinecone.io/reference/api/2025-10/data-plane/deletenamespace.md): Delete a namespace from a serverless index. Deleting a namespace is irreversible; all data in the namespace is permanently deleted. ##### Vectors - [Upsert vectors](https://docs.pinecone.io/reference/api/2025-10/data-plane/upsert.md): Upsert vectors into a namespace. If a new value is upserted for an existing vector ID, it will overwrite the previous value. - [Upsert text](https://docs.pinecone.io/reference/api/2025-10/data-plane/upsert_records.md): Upsert text into a namespace. Pinecone converts the text to vectors automatically using the hosted embedding model associated with the index. - [Fetch vectors](https://docs.pinecone.io/reference/api/2025-10/data-plane/fetch.md): Look up and return vectors by ID from a single namespace. The returned vectors include the vector data and/or metadata. - [Fetch vectors by metadata](https://docs.pinecone.io/reference/api/2025-10/data-plane/fetch_by_metadata.md): Look up and return vectors by metadata filter from a single namespace. The returned vectors include the vector data and/or metadata. For guidance and examples, see [Fetch data](https://docs.pinecone.io/guides/manage-data/fetch-data). - [Update a vector](https://docs.pinecone.io/reference/api/2025-10/data-plane/update.md): Update a vector in a namespace. If a value is included, it will overwrite the previous value. If a `set_metadata` is included, the values of the fields specified in it will be added or overwrite the previous value. - [Delete vectors](https://docs.pinecone.io/reference/api/2025-10/data-plane/delete.md): Delete vectors by id from a single namespace. - [List vector IDs](https://docs.pinecone.io/reference/api/2025-10/data-plane/list.md): List the IDs of vectors in a single namespace of a serverless index. An optional prefix can be passed to limit the results to IDs with a common prefix. ##### Search - [Search with a vector](https://docs.pinecone.io/reference/api/2025-10/data-plane/query.md): Search a namespace using a query vector. It retrieves the ids of the most similar items in a namespace, along with their similarity scores. - [Search with text](https://docs.pinecone.io/reference/api/2025-10/data-plane/search_records.md): Search a namespace with a query text, query vector, or record ID and return the most similar records, along with their similarity scores. Optionally, rerank the initial results based on their relevance to the query. ##### Imports - [Start import](https://docs.pinecone.io/reference/api/2025-10/data-plane/start_import.md): Start an asynchronous import of vectors from object storage into an index. - [List imports](https://docs.pinecone.io/reference/api/2025-10/data-plane/list_imports.md): List all recent and ongoing import operations. - [Describe an import](https://docs.pinecone.io/reference/api/2025-10/data-plane/describe_import.md): Return details of a specific import operation. - [Cancel an import](https://docs.pinecone.io/reference/api/2025-10/data-plane/cancel_import.md): Cancel an import operation if it is not yet finished. It has no effect if the operation is already finished. ##### Backups - [Create a backup of an index](https://docs.pinecone.io/reference/api/2025-10/control-plane/create_backup.md): Create a backup of an index. - [List backups for all indexes in a project](https://docs.pinecone.io/reference/api/2025-10/control-plane/list_project_backups.md): List all backups for a project. - [List backups for an index](https://docs.pinecone.io/reference/api/2025-10/control-plane/list_index_backups.md): List all backups for an index. - [Describe a backup](https://docs.pinecone.io/reference/api/2025-10/control-plane/describe_backup.md): Get a description of a backup. - [Delete a backup](https://docs.pinecone.io/reference/api/2025-10/control-plane/delete_backup.md): Delete a backup. - [Create an index from a backup](https://docs.pinecone.io/reference/api/2025-10/control-plane/create_index_from_backup.md): Create an index from a backup. - [List restore jobs](https://docs.pinecone.io/reference/api/2025-10/control-plane/list_restore_jobs.md): List all restore jobs for a project. - [Describe a restore job](https://docs.pinecone.io/reference/api/2025-10/control-plane/describe_restore_job.md): Get a description of a restore job. - [List collections](https://docs.pinecone.io/reference/api/2025-10/control-plane/list_collections.md): List all collections in a project. Serverless indexes do not support collections. - [Create a collection](https://docs.pinecone.io/reference/api/2025-10/control-plane/create_collection.md): Create a Pinecone collection. Serverless indexes do not support collections. - [Describe a collection](https://docs.pinecone.io/reference/api/2025-10/control-plane/describe_collection.md): Get a description of a collection. Serverless indexes do not support collections. - [Delete a collection](https://docs.pinecone.io/reference/api/2025-10/control-plane/delete_collection.md): Delete an existing collection. Serverless indexes do not support collections. #### Inference ##### Embed - [Generate vectors](https://docs.pinecone.io/reference/api/2025-10/inference/generate-embeddings.md): Generate vector embeddings for input data. This endpoint uses Pinecone's [hosted embedding models](https://docs.pinecone.io/guides/index-data/create-an-index#embedding-models). ##### Rerank - [Rerank results](https://docs.pinecone.io/reference/api/2025-10/inference/rerank.md): Rerank results according to their relevance to a query. ##### Models - [List available models](https://docs.pinecone.io/reference/api/2025-10/inference/list_models.md): List the embedding and reranking models hosted by Pinecone. - [Describe a model](https://docs.pinecone.io/reference/api/2025-10/inference/describe_model.md): Get a description of a model hosted by Pinecone. #### Admin ##### API keys - [Create an API key](https://docs.pinecone.io/reference/api/2025-10/admin/create_api_key.md): Create a new API key for a project. Developers can use the API key to authenticate requests to Pinecone's Data Plane and Control Plane APIs. - [List API keys](https://docs.pinecone.io/reference/api/2025-10/admin/list_api_keys.md): List all API keys in a project. - [Get API key details](https://docs.pinecone.io/reference/api/2025-10/admin/fetch_api_key.md): Get the details of an API key, excluding the API key secret. - [Update an API key](https://docs.pinecone.io/reference/api/2025-10/admin/update_api_key.md): Update the name and roles of an API key. - [Delete an API key](https://docs.pinecone.io/reference/api/2025-10/admin/delete_api_key.md): Delete an API key from a project. ##### Projects - [Create a new project](https://docs.pinecone.io/reference/api/2025-10/admin/create_project.md): Creates a new project. - [List projects](https://docs.pinecone.io/reference/api/2025-10/admin/list_projects.md): List all projects in an organization. - [Get project details](https://docs.pinecone.io/reference/api/2025-10/admin/fetch_project.md): Get details about a project. - [Update a project](https://docs.pinecone.io/reference/api/2025-10/admin/update_project.md): Update a project's configuration details. You can update the project's name, maximum number of Pods, or enable encryption with a customer-managed encryption key (CMEK). - [Delete a project](https://docs.pinecone.io/reference/api/2025-10/admin/delete_project.md): Delete a project and all its associated configuration. Before deleting a project, you must delete all indexes, assistants, backups, and collections associated with the project. Other project resources, such as API keys, are automatically deleted when the project is deleted. ##### Service accounts - [Create an access token](https://docs.pinecone.io/reference/api/2025-10/admin/get_token.md): Obtain an access token for a service account using the OAuth2 client credentials flow. An access token is needed to authorize requests to the Pinecone Admin API. The host domain for OAuth endpoints is `login.pinecone.io`. #### SDKs - [Pinecone SDKs overview](https://docs.pinecone.io/reference/pinecone-sdks.md): Browse official Pinecone SDKs for Python, Node.js, Java, and Go, including the version mappings between SDK releases and API versions. ##### Python - [Pinecone Python SDK](https://docs.pinecone.io/reference/sdks/python/overview.md): Install and use the Pinecone SDK for Pinecone Python SDK: auth, typed clients, and API operations. For installation instructions, usage examples, and. - [Reference](https://docs.pinecone.io/reference/sdks/python/reference.md): Reference documentation for the Pinecone Python SDK, including client setup, types, and methods for managing indexes and vector data operations. ##### Node.js - [Pinecone Node.js SDK](https://docs.pinecone.io/reference/sdks/node/overview.md): Install and use the Pinecone Node.js and TypeScript SDK to manage indexes, upsert vectors, run semantic search, and call the Admin and Inference APIs. - [Reference](https://docs.pinecone.io/reference/sdks/node/reference.md): Reference documentation for the Pinecone Node.js SDK, including client setup, types, and methods for managing indexes and vector data operations. ##### Java - [Pinecone Java SDK](https://docs.pinecone.io/reference/sdks/java/overview.md): Install and use the Pinecone Java SDK to manage indexes and namespaces, upsert vectors, run semantic search, and call the Admin and Inference APIs from Java. - [Reference](https://docs.pinecone.io/reference/sdks/java/reference.md): Reference documentation for the Pinecone Java SDK, including client setup, types, and methods for managing indexes and vector data operations. - [OpenTelemetry support](https://docs.pinecone.io/reference/sdks/java/open-telemetry.md): Monitor Pinecone Java SDK operations with OpenTelemetry metrics for client latency, server processing time, and errors via Prometheus. ##### Go - [Pinecone Go SDK](https://docs.pinecone.io/reference/sdks/go/overview.md): Install and use the Pinecone Go SDK to manage indexes and namespaces, upsert vectors, run semantic search, and call the Admin and Inference APIs from Go. - [Reference](https://docs.pinecone.io/reference/sdks/go/reference.md): Reference documentation for the Pinecone Go SDK, including client setup, types, and methods for managing indexes and vector data operations. #### CLI - [CLI quickstart](https://docs.pinecone.io/reference/cli/quickstart.md): Pinecone CLI quickstart for installing pc, authenticating, and managing indexes, vectors, and data imports directly from your terminal. - [CLI command reference](https://docs.pinecone.io/reference/cli/command-reference.md): Complete Pinecone CLI command reference covering syntax, subcommands, flags, help output, and exit codes for auth, index, and project. - [CLI authentication](https://docs.pinecone.io/reference/cli/authentication.md): Authenticate the Pinecone CLI using user login, service accounts, or API keys, including auth priority and Admin API access rules. - [CLI target context](https://docs.pinecone.io/reference/cli/target-context.md): Set the Pinecone CLI target context with pc target to control which organization and project your commands run against, including in CI/CD and JSON mode. #### Tools - [Spark-Pinecone connector](https://docs.pinecone.io/reference/tools/pinecone-spark-connector.md): Pinecone data tools: Use the connector to efficiently create, ingest, and update vector embeddings at scale with Databricks and Pinecone. ### 2025-04 #### APIs - [API reference](https://docs.pinecone.io/reference/api/introduction.md): Pinecone API reference overview for Database, Inference, and Admin endpoints with supported SDKs including Python, Node.js, Java, and Go. - [Authentication](https://docs.pinecone.io/reference/api/authentication.md): Pinecone API authentication guide covering API key generation, SDK client setup, and HTTP header configuration for authorized requests. - [Pinecone API versioning](https://docs.pinecone.io/reference/api/versioning.md): Learn how Pinecone versions its APIs by release date, how long each stable version is supported, and how to set the X-Pinecone-Api-Version header. - [Errors](https://docs.pinecone.io/reference/api/errors.md): Look up the HTTP status codes the Pinecone API returns, what each 2xx success and 4xx or 5xx error means, and where to handle them in production. ##### Database limits - [Pinecone Database limits overview](https://docs.pinecone.io/reference/api/database-limits.md): Reference for Pinecone Database rate, object, operation, and identifier limits, plus known index and serverless limitations. - [Rate limits](https://docs.pinecone.io/reference/api/database-limits/rate-limits.md): Request-per-second, monthly usage, and model throughput limits for Pinecone Database serverless indexes, and the 429 errors returned when you exceed them. - [Object limits](https://docs.pinecone.io/reference/api/database-limits/object-limits.md): Limits on the number and size of Pinecone Database projects, indexes, namespaces, storage, backups, and collections, by plan. - [Operation limits](https://docs.pinecone.io/reference/api/database-limits/operation-limits.md): Fixed limits on Pinecone Database operations, including upsert, update, import, query, fetch, and delete batch sizes and metadata filter expressions. - [Identifier limits](https://docs.pinecone.io/reference/api/database-limits/identifier-limits.md): Maximum length and allowed characters for Pinecone identifiers, including organization, project, index, namespace, and record names. - [Known limitations](https://docs.pinecone.io/reference/api/known-limitations.md): Known limitations and feature restrictions for Pinecone indexes, including upsert consistency, metadata rules, and serverless caveats. #### Database ##### Indexes - [List indexes](https://docs.pinecone.io/reference/api/2025-04/control-plane/list_indexes.md): List all indexes in a project. - [Create an index](https://docs.pinecone.io/reference/api/2025-04/control-plane/create_index.md): Create a Pinecone index. This is where you specify the measure of similarity, the dimension of vectors to be stored in the index, which cloud provider you would like to deploy with, and more. For guidance and examples, see [Create an index](https://docs.pinecone.io/guides/index-data/create-an-ind… - [Create an index with integrated embedding](https://docs.pinecone.io/reference/api/2025-04/control-plane/create_for_model.md): Create an index with integrated embedding. - [Describe an index](https://docs.pinecone.io/reference/api/2025-04/control-plane/describe_index.md): Get a description of an index. - [Delete an index](https://docs.pinecone.io/reference/api/2025-04/control-plane/delete_index.md): Delete an existing index. - [Configure an index](https://docs.pinecone.io/reference/api/2025-04/control-plane/configure_index.md): Configure an existing index. For serverless indexes, you can configure index deletion protection, tags, and integrated inference embedding settings for the index. For pod-based indexes, you can configure the pod size, number of replicas, tags, and index deletion protection. - [Get index stats](https://docs.pinecone.io/reference/api/2025-04/data-plane/describeindexstats.md): Return statistics about the contents of an index, including the vector count per namespace, the number of dimensions, and the index fullness. ##### Namespaces - [List namespaces](https://docs.pinecone.io/reference/api/2025-04/data-plane/listnamespaces.md): List all namespaces in a serverless index. - [Describe a namespace](https://docs.pinecone.io/reference/api/2025-04/data-plane/describenamespace.md): Describe a namespace in a serverless index, including the total number of vectors in the namespace. - [Delete a namespace](https://docs.pinecone.io/reference/api/2025-04/data-plane/deletenamespace.md): Delete a namespace from a serverless index. Deleting a namespace is irreversible; all data in the namespace is permanently deleted. ##### Vectors - [Upsert vectors](https://docs.pinecone.io/reference/api/2025-04/data-plane/upsert.md): Upsert vectors into a namespace. If a new value is upserted for an existing vector ID, it will overwrite the previous value. - [Upsert text](https://docs.pinecone.io/reference/api/2025-04/data-plane/upsert_records.md): Upsert text into a namespace. Pinecone converts the text to vectors automatically using the hosted embedding model associated with the index. - [Fetch vectors](https://docs.pinecone.io/reference/api/2025-04/data-plane/fetch.md): Look up and return vectors by ID from a single namespace. The returned vectors include the vector data and/or metadata. - [Update a vector](https://docs.pinecone.io/reference/api/2025-04/data-plane/update.md): Update a vector in a namespace. If a value is included, it will overwrite the previous value. If a `set_metadata` is included, the values of the fields specified in it will be added or overwrite the previous value. - [Delete vectors](https://docs.pinecone.io/reference/api/2025-04/data-plane/delete.md): Delete vectors by id from a single namespace. - [List vector IDs](https://docs.pinecone.io/reference/api/2025-04/data-plane/list.md): List the IDs of vectors in a single namespace of a serverless index. An optional prefix can be passed to limit the results to IDs with a common prefix. ##### Search - [Search with a vector](https://docs.pinecone.io/reference/api/2025-04/data-plane/query.md): Search a namespace using a query vector. It retrieves the ids of the most similar items in a namespace, along with their similarity scores. - [Search with text](https://docs.pinecone.io/reference/api/2025-04/data-plane/search_records.md): Search a namespace with a query text, query vector, or record ID and return the most similar records, along with their similarity scores. Optionally, rerank the initial results based on their relevance to the query. ##### Imports - [Start import](https://docs.pinecone.io/reference/api/2025-04/data-plane/start_import.md): Start an asynchronous import of vectors from object storage into an index. - [List imports](https://docs.pinecone.io/reference/api/2025-04/data-plane/list_imports.md): List all recent and ongoing import operations. - [Describe an import](https://docs.pinecone.io/reference/api/2025-04/data-plane/describe_import.md): Return details of a specific import operation. - [Cancel an import](https://docs.pinecone.io/reference/api/2025-04/data-plane/cancel_import.md): Cancel an import operation if it is not yet finished. It has no effect if the operation is already finished. ##### Backups - [Create a backup of an index](https://docs.pinecone.io/reference/api/2025-04/control-plane/create_backup.md): Create a backup of an index. - [List backups for all indexes in a project](https://docs.pinecone.io/reference/api/2025-04/control-plane/list_project_backups.md): List all backups for a project. - [List backups for an index](https://docs.pinecone.io/reference/api/2025-04/control-plane/list_index_backups.md): List all backups for an index. - [Describe a backup](https://docs.pinecone.io/reference/api/2025-04/control-plane/describe_backup.md): Get a description of a backup. - [Delete a backup](https://docs.pinecone.io/reference/api/2025-04/control-plane/delete_backup.md): Delete a backup. - [Create an index from a backup](https://docs.pinecone.io/reference/api/2025-04/control-plane/create_index_from_backup.md): Create an index from a backup. - [List restore jobs](https://docs.pinecone.io/reference/api/2025-04/control-plane/list_restore_jobs.md): List all restore jobs for a project. - [Describe a restore job](https://docs.pinecone.io/reference/api/2025-04/control-plane/describe_restore_job.md): Get a description of a restore job. - [List collections](https://docs.pinecone.io/reference/api/2025-04/control-plane/list_collections.md): List all collections in a project. Serverless indexes do not support collections. - [Create a collection](https://docs.pinecone.io/reference/api/2025-04/control-plane/create_collection.md): Create a Pinecone collection. Serverless indexes do not support collections. - [Describe a collection](https://docs.pinecone.io/reference/api/2025-04/control-plane/describe_collection.md): Get a description of a collection. Serverless indexes do not support collections. - [Delete a collection](https://docs.pinecone.io/reference/api/2025-04/control-plane/delete_collection.md): Delete an existing collection. Serverless indexes do not support collections. #### Inference ##### Embed - [Generate vectors](https://docs.pinecone.io/reference/api/2025-04/inference/generate-embeddings.md): Generate vector embeddings for input data. This endpoint uses Pinecone's [hosted embedding models](https://docs.pinecone.io/guides/index-data/create-an-index#embedding-models). ##### Rerank - [Rerank documents](https://docs.pinecone.io/reference/api/2025-04/inference/rerank.md): Rerank results according to their relevance to a query. ##### Models - [List available models](https://docs.pinecone.io/reference/api/2025-04/inference/list_models.md): List the embedding and reranking models hosted by Pinecone. - [Describe a model](https://docs.pinecone.io/reference/api/2025-04/inference/describe_model.md): Get a description of a model hosted by Pinecone. #### Admin ##### API keys - [Create an API key](https://docs.pinecone.io/reference/api/2025-04/admin/create_api_key.md): Create a new API key for a project. Developers can use the API key to authenticate requests to Pinecone's Data Plane and Control Plane APIs. - [List API keys](https://docs.pinecone.io/reference/api/2025-04/admin/list_api_keys.md): List all API keys in a project. - [Get API key details](https://docs.pinecone.io/reference/api/2025-04/admin/fetch_api_key.md): Get the details of an API key, excluding the API key secret. - [Update an API key](https://docs.pinecone.io/reference/api/2025-04/admin/update_api_key.md): Update the name and roles of an API key. - [Delete an API key](https://docs.pinecone.io/reference/api/2025-04/admin/delete_api_key.md): Delete an API key from a project. ##### Projects - [Create a new project](https://docs.pinecone.io/reference/api/2025-04/admin/create_project.md): Creates a new project. - [List projects](https://docs.pinecone.io/reference/api/2025-04/admin/list_projects.md): List all projects in an organization. - [Get project details](https://docs.pinecone.io/reference/api/2025-04/admin/fetch_project.md): Get details about a project. - [Update a project](https://docs.pinecone.io/reference/api/2025-04/admin/update_project.md): Update a project's configuration details. You can update the project's name, maximum number of Pods, or enable encryption with a customer-managed encryption key (CMEK). - [Delete a project](https://docs.pinecone.io/reference/api/2025-04/admin/delete_project.md): Delete a project and all its associated configuration. Before deleting a project, you must delete all indexes, assistants, backups, and collections associated with the project. Other project resources, such as API keys, are automatically deleted when the project is deleted. ##### Service accounts - [Get an access token](https://docs.pinecone.io/reference/api/2025-04/admin/get_token.md): Obtain an access token for a service account using the OAuth2 client credentials flow. An access token is needed to authorize requests to the Pinecone Admin API. The host domain for OAuth endpoints is `login.pinecone.io`. #### SDKs - [Pinecone SDKs overview](https://docs.pinecone.io/reference/pinecone-sdks.md): Browse official Pinecone SDKs for Python, Node.js, Java, and Go, including the version mappings between SDK releases and API versions. ##### Python - [Pinecone Python SDK](https://docs.pinecone.io/reference/sdks/python/overview.md): Install and use the Pinecone SDK for Pinecone Python SDK: auth, typed clients, and API operations. For installation instructions, usage examples, and. - [Reference](https://docs.pinecone.io/reference/sdks/python/reference.md): Reference documentation for the Pinecone Python SDK, including client setup, types, and methods for managing indexes and vector data operations. ##### Node.js - [Pinecone Node.js SDK](https://docs.pinecone.io/reference/sdks/node/overview.md): Install and use the Pinecone Node.js and TypeScript SDK to manage indexes, upsert vectors, run semantic search, and call the Admin and Inference APIs. - [Reference](https://docs.pinecone.io/reference/sdks/node/reference.md): Reference documentation for the Pinecone Node.js SDK, including client setup, types, and methods for managing indexes and vector data operations. ##### Java - [Pinecone Java SDK](https://docs.pinecone.io/reference/sdks/java/overview.md): Install and use the Pinecone Java SDK to manage indexes and namespaces, upsert vectors, run semantic search, and call the Admin and Inference APIs from Java. - [Reference](https://docs.pinecone.io/reference/sdks/java/reference.md): Reference documentation for the Pinecone Java SDK, including client setup, types, and methods for managing indexes and vector data operations. - [OpenTelemetry support](https://docs.pinecone.io/reference/sdks/java/open-telemetry.md): Monitor Pinecone Java SDK operations with OpenTelemetry metrics for client latency, server processing time, and errors via Prometheus. ##### Go - [Pinecone Go SDK](https://docs.pinecone.io/reference/sdks/go/overview.md): Install and use the Pinecone Go SDK to manage indexes and namespaces, upsert vectors, run semantic search, and call the Admin and Inference APIs from Go. - [Reference](https://docs.pinecone.io/reference/sdks/go/reference.md): Reference documentation for the Pinecone Go SDK, including client setup, types, and methods for managing indexes and vector data operations. #### CLI - [CLI quickstart](https://docs.pinecone.io/reference/cli/quickstart.md): Pinecone CLI quickstart for installing pc, authenticating, and managing indexes, vectors, and data imports directly from your terminal. - [CLI command reference](https://docs.pinecone.io/reference/cli/command-reference.md): Complete Pinecone CLI command reference covering syntax, subcommands, flags, help output, and exit codes for auth, index, and project. - [CLI authentication](https://docs.pinecone.io/reference/cli/authentication.md): Authenticate the Pinecone CLI using user login, service accounts, or API keys, including auth priority and Admin API access rules. - [CLI target context](https://docs.pinecone.io/reference/cli/target-context.md): Set the Pinecone CLI target context with pc target to control which organization and project your commands run against, including in CI/CD and JSON mode. #### Tools - [Spark-Pinecone connector](https://docs.pinecone.io/reference/tools/pinecone-spark-connector.md): Pinecone data tools: Use the connector to efficiently create, ingest, and update vector embeddings at scale with Databricks and Pinecone. ### 2025-01 #### APIs - [API reference](https://docs.pinecone.io/reference/api/introduction.md): Pinecone API reference overview for Database, Inference, and Admin endpoints with supported SDKs including Python, Node.js, Java, and Go. - [Authentication](https://docs.pinecone.io/reference/api/authentication.md): Pinecone API authentication guide covering API key generation, SDK client setup, and HTTP header configuration for authorized requests. - [Pinecone API versioning](https://docs.pinecone.io/reference/api/versioning.md): Learn how Pinecone versions its APIs by release date, how long each stable version is supported, and how to set the X-Pinecone-Api-Version header. - [Errors](https://docs.pinecone.io/reference/api/errors.md): Look up the HTTP status codes the Pinecone API returns, what each 2xx success and 4xx or 5xx error means, and where to handle them in production. ##### Database limits - [Pinecone Database limits overview](https://docs.pinecone.io/reference/api/database-limits.md): Reference for Pinecone Database rate, object, operation, and identifier limits, plus known index and serverless limitations. - [Rate limits](https://docs.pinecone.io/reference/api/database-limits/rate-limits.md): Request-per-second, monthly usage, and model throughput limits for Pinecone Database serverless indexes, and the 429 errors returned when you exceed them. - [Object limits](https://docs.pinecone.io/reference/api/database-limits/object-limits.md): Limits on the number and size of Pinecone Database projects, indexes, namespaces, storage, backups, and collections, by plan. - [Operation limits](https://docs.pinecone.io/reference/api/database-limits/operation-limits.md): Fixed limits on Pinecone Database operations, including upsert, update, import, query, fetch, and delete batch sizes and metadata filter expressions. - [Identifier limits](https://docs.pinecone.io/reference/api/database-limits/identifier-limits.md): Maximum length and allowed characters for Pinecone identifiers, including organization, project, index, namespace, and record names. - [Known limitations](https://docs.pinecone.io/reference/api/known-limitations.md): Known limitations and feature restrictions for Pinecone indexes, including upsert consistency, metadata rules, and serverless caveats. #### Database ##### Indexes - [List indexes](https://docs.pinecone.io/reference/api/2025-01/control-plane/list_indexes.md): This operation returns a list of all indexes in a project. - [Create an index](https://docs.pinecone.io/reference/api/2025-01/control-plane/create_index.md): Create an index for vectors created with an external embedding model. - [Create an index with integrated embedding](https://docs.pinecone.io/reference/api/2025-01/control-plane/create_for_model.md): Create an index with integrated embedding. - [Describe an index](https://docs.pinecone.io/reference/api/2025-01/control-plane/describe_index.md): Get a description of an index. - [Delete an index](https://docs.pinecone.io/reference/api/2025-01/control-plane/delete_index.md): Delete an existing index. - [Configure an index](https://docs.pinecone.io/reference/api/2025-01/control-plane/configure_index.md): Configure an existing index. - [Get index stats](https://docs.pinecone.io/reference/api/2025-01/data-plane/describeindexstats.md): Return statistics about the contents of an index, including the vector count per namespace, the number of dimensions, and the index fullness. ##### Vectors - [Upsert vectors](https://docs.pinecone.io/reference/api/2025-01/data-plane/upsert.md): Upsert vectors into a namespace. If a new value is upserted for an existing vector ID, it will overwrite the previous value. - [Upsert text](https://docs.pinecone.io/reference/api/2025-01/data-plane/upsert_records.md): Upsert text into a namespace. Pinecone converts the text to vectors automatically using the hosted embedding model associated with the index. - [Fetch vectors](https://docs.pinecone.io/reference/api/2025-01/data-plane/fetch.md): Look up and return vectors, by ID, from a single namespace. The returned vectors include the vector data and/or metadata. - [Update a vector](https://docs.pinecone.io/reference/api/2025-01/data-plane/update.md): Update a vector in a namespace. If a value is included, it will overwrite the previous value. If a `set_metadata` is included, the values of the fields specified in it will be added or overwrite the previous value. - [Delete vectors](https://docs.pinecone.io/reference/api/2025-01/data-plane/delete.md): Delete vectors, by id, from a single namespace. - [List vector IDs](https://docs.pinecone.io/reference/api/2025-01/data-plane/list.md): List the IDs of vectors in a single namespace of a serverless index. An optional prefix can be passed to limit the results to IDs with a common prefix. ##### Search - [Search with a vector](https://docs.pinecone.io/reference/api/2025-01/data-plane/query.md): Search a namespace with a query vector or record ID and return the IDs of the most similar records, along with their similarity scores. - [Search with text](https://docs.pinecone.io/reference/api/2025-01/data-plane/search_records.md): Search a namespace with a query text, query vector, or record ID and return the most similar records, along with their similarity scores. Optionally, rerank the initial results based on their relevance to the query. ##### Imports - [Start import](https://docs.pinecone.io/reference/api/2025-01/data-plane/start_import.md): Start an asynchronous import of vectors from object storage into an index. - [List imports](https://docs.pinecone.io/reference/api/2025-01/data-plane/list_imports.md): List all recent and ongoing import operations. - [Describe an import](https://docs.pinecone.io/reference/api/2025-01/data-plane/describe_import.md): Return details of a specific import operation. - [Cancel an import](https://docs.pinecone.io/reference/api/2025-01/data-plane/cancel_import.md): Cancel an import operation if it is not yet finished. It has no effect if the operation is already finished. ##### Backups - [List collections](https://docs.pinecone.io/reference/api/2025-01/control-plane/list_collections.md): This operation returns a list of all collections in a project. Serverless indexes do not support collections. - [Create a collection](https://docs.pinecone.io/reference/api/2025-01/control-plane/create_collection.md): This operation creates a Pinecone collection. Serverless indexes do not support collections. - [Describe a collection](https://docs.pinecone.io/reference/api/2025-01/control-plane/describe_collection.md): This operation gets a description of a collection. Serverless indexes do not support collections. - [Delete a collection](https://docs.pinecone.io/reference/api/2025-01/control-plane/delete_collection.md): This operation deletes an existing collection. Serverless indexes do not support collections. #### Inference ##### Embed - [Generate vectors](https://docs.pinecone.io/reference/api/2025-01/inference/generate-embeddings.md): Generate vector embeddings for input data. This endpoint uses Pinecone's [hosted embedding models](https://docs.pinecone.io/guides/index-data/create-an-index#embedding-models). ##### Rerank - [Rerank results](https://docs.pinecone.io/reference/api/2025-01/inference/rerank.md): Rerank query results according to their relevance to a query. This endpoint uses [Pinecone Inference](https://docs.pinecone.io/guides/index-data/indexing-overview#vector-embedding). #### SDKs - [Pinecone SDKs overview](https://docs.pinecone.io/reference/pinecone-sdks.md): Browse official Pinecone SDKs for Python, Node.js, Java, and Go, including the version mappings between SDK releases and API versions. ##### Python - [Pinecone Python SDK](https://docs.pinecone.io/reference/sdks/python/overview.md): Install and use the Pinecone SDK for Pinecone Python SDK: auth, typed clients, and API operations. For installation instructions, usage examples, and. - [Reference](https://docs.pinecone.io/reference/sdks/python/reference.md): Reference documentation for the Pinecone Python SDK, including client setup, types, and methods for managing indexes and vector data operations. ##### Node.js - [Pinecone Node.js SDK](https://docs.pinecone.io/reference/sdks/node/overview.md): Install and use the Pinecone Node.js and TypeScript SDK to manage indexes, upsert vectors, run semantic search, and call the Admin and Inference APIs. - [Reference](https://docs.pinecone.io/reference/sdks/node/reference.md): Reference documentation for the Pinecone Node.js SDK, including client setup, types, and methods for managing indexes and vector data operations. ##### Java - [Pinecone Java SDK](https://docs.pinecone.io/reference/sdks/java/overview.md): Install and use the Pinecone Java SDK to manage indexes and namespaces, upsert vectors, run semantic search, and call the Admin and Inference APIs from Java. - [Reference](https://docs.pinecone.io/reference/sdks/java/reference.md): Reference documentation for the Pinecone Java SDK, including client setup, types, and methods for managing indexes and vector data operations. - [OpenTelemetry support](https://docs.pinecone.io/reference/sdks/java/open-telemetry.md): Monitor Pinecone Java SDK operations with OpenTelemetry metrics for client latency, server processing time, and errors via Prometheus. ##### Go - [Pinecone Go SDK](https://docs.pinecone.io/reference/sdks/go/overview.md): Install and use the Pinecone Go SDK to manage indexes and namespaces, upsert vectors, run semantic search, and call the Admin and Inference APIs from Go. - [Reference](https://docs.pinecone.io/reference/sdks/go/reference.md): Reference documentation for the Pinecone Go SDK, including client setup, types, and methods for managing indexes and vector data operations. #### CLI - [CLI quickstart](https://docs.pinecone.io/reference/cli/quickstart.md): Pinecone CLI quickstart for installing pc, authenticating, and managing indexes, vectors, and data imports directly from your terminal. - [CLI command reference](https://docs.pinecone.io/reference/cli/command-reference.md): Complete Pinecone CLI command reference covering syntax, subcommands, flags, help output, and exit codes for auth, index, and project. - [CLI authentication](https://docs.pinecone.io/reference/cli/authentication.md): Authenticate the Pinecone CLI using user login, service accounts, or API keys, including auth priority and Admin API access rules. - [CLI target context](https://docs.pinecone.io/reference/cli/target-context.md): Set the Pinecone CLI target context with pc target to control which organization and project your commands run against, including in CI/CD and JSON mode. #### Tools - [Spark-Pinecone connector](https://docs.pinecone.io/reference/tools/pinecone-spark-connector.md): Pinecone data tools: Use the connector to efficiently create, ingest, and update vector embeddings at scale with Databricks and Pinecone. ### 2024-10 #### APIs - [API reference](https://docs.pinecone.io/reference/api/introduction.md): Pinecone API reference overview for Database, Inference, and Admin endpoints with supported SDKs including Python, Node.js, Java, and Go. - [Authentication](https://docs.pinecone.io/reference/api/authentication.md): Pinecone API authentication guide covering API key generation, SDK client setup, and HTTP header configuration for authorized requests. - [Pinecone API versioning](https://docs.pinecone.io/reference/api/versioning.md): Learn how Pinecone versions its APIs by release date, how long each stable version is supported, and how to set the X-Pinecone-Api-Version header. - [Errors](https://docs.pinecone.io/reference/api/errors.md): Look up the HTTP status codes the Pinecone API returns, what each 2xx success and 4xx or 5xx error means, and where to handle them in production. ##### Database limits - [Pinecone Database limits overview](https://docs.pinecone.io/reference/api/database-limits.md): Reference for Pinecone Database rate, object, operation, and identifier limits, plus known index and serverless limitations. - [Rate limits](https://docs.pinecone.io/reference/api/database-limits/rate-limits.md): Request-per-second, monthly usage, and model throughput limits for Pinecone Database serverless indexes, and the 429 errors returned when you exceed them. - [Object limits](https://docs.pinecone.io/reference/api/database-limits/object-limits.md): Limits on the number and size of Pinecone Database projects, indexes, namespaces, storage, backups, and collections, by plan. - [Operation limits](https://docs.pinecone.io/reference/api/database-limits/operation-limits.md): Fixed limits on Pinecone Database operations, including upsert, update, import, query, fetch, and delete batch sizes and metadata filter expressions. - [Identifier limits](https://docs.pinecone.io/reference/api/database-limits/identifier-limits.md): Maximum length and allowed characters for Pinecone identifiers, including organization, project, index, namespace, and record names. - [Known limitations](https://docs.pinecone.io/reference/api/known-limitations.md): Known limitations and feature restrictions for Pinecone indexes, including upsert consistency, metadata rules, and serverless caveats. #### Database ##### Indexes - [List indexes](https://docs.pinecone.io/reference/api/2024-10/control-plane/list_indexes.md): This operation returns a list of all indexes in a project. - [Create an index](https://docs.pinecone.io/reference/api/2024-10/control-plane/create_index.md): Create an index for vectors created with an external embedding model. For guidance and examples, see [Create an index](https://docs.pinecone.io/guides/index-data/create-an-index). - [Describe an index](https://docs.pinecone.io/reference/api/2024-10/control-plane/describe_index.md): Get a description of an index. - [Delete an index](https://docs.pinecone.io/reference/api/2024-10/control-plane/delete_index.md): Delete an existing index. - [Configure an index](https://docs.pinecone.io/reference/api/2024-10/control-plane/configure_index.md): Configure an existing index. - [Get index stats](https://docs.pinecone.io/reference/api/2024-10/data-plane/describeindexstats.md): The `describe_index_stats` operation returns statistics about the contents of an index, including the vector count per namespace, the number of dimensions, and the index fullness. ##### Vectors - [Upsert vectors](https://docs.pinecone.io/reference/api/2024-10/data-plane/upsert.md): The `upsert` operation writes vectors into a namespace. If a new value is upserted for an existing vector ID, it will overwrite the previous value. - [Search with a vector](https://docs.pinecone.io/reference/api/2024-10/data-plane/query.md): The `query` operation searches a namespace, using a query vector. It retrieves the ids of the most similar items in a namespace, along with their similarity scores. - [Fetch vectors](https://docs.pinecone.io/reference/api/2024-10/data-plane/fetch.md): The `fetch` operation looks up and returns vectors, by ID, from a single namespace. The returned vectors include the vector data and/or metadata. - [Update a vector](https://docs.pinecone.io/reference/api/2024-10/data-plane/update.md): The `update` operation updates a vector in a namespace. If a value is included, it will overwrite the previous value. If a `set_metadata` is included, the values of the fields specified in it will be added or overwrite the previous value. - [Delete vectors](https://docs.pinecone.io/reference/api/2024-10/data-plane/delete.md): The `delete` operation deletes vectors, by id, from a single namespace. - [List vector IDs](https://docs.pinecone.io/reference/api/2024-10/data-plane/list.md): The `list` operation lists the IDs of vectors in a single namespace of a serverless index. An optional prefix can be passed to limit the results to IDs with a common prefix. ##### Imports - [Start import](https://docs.pinecone.io/reference/api/2024-10/data-plane/start_import.md): The `start_import` operation starts an asynchronous import of vectors from object storage into an index. - [List imports](https://docs.pinecone.io/reference/api/2024-10/data-plane/list_imports.md): The `list_imports` operation lists all recent and ongoing import operations. - [Describe an import](https://docs.pinecone.io/reference/api/2024-10/data-plane/describe_import.md): The `describe_import` operation returns details of a specific import operation. - [Cancel an import](https://docs.pinecone.io/reference/api/2024-10/data-plane/cancel_import.md): The `cancel_import` operation cancels an import operation if it is not yet finished. It has no effect if the operation is already finished. ##### Backups - [List collections](https://docs.pinecone.io/reference/api/2024-10/control-plane/list_collections.md): This operation returns a list of all collections in a project. Serverless indexes do not support collections. - [Create a collection](https://docs.pinecone.io/reference/api/2024-10/control-plane/create_collection.md): This operation creates a Pinecone collection. Serverless indexes do not support collections. - [Describe a collection](https://docs.pinecone.io/reference/api/2024-10/control-plane/describe_collection.md): This operation gets a description of a collection. Serverless indexes do not support collections. - [Delete a collection](https://docs.pinecone.io/reference/api/2024-10/control-plane/delete_collection.md): This operation deletes an existing collection. Serverless indexes do not support collections. #### Inference - [Generate vectors](https://docs.pinecone.io/reference/api/2024-10/inference/generate-embeddings.md): Generate vector embeddings for input data. This endpoint uses Pinecone's [hosted embedding models](https://docs.pinecone.io/guides/index-data/create-an-index#embedding-models). - [Rerank results](https://docs.pinecone.io/reference/api/2024-10/inference/rerank.md): Rerank query results according to their relevance to a query. This endpoint uses [Pinecone Inference](https://docs.pinecone.io/guides/index-data/indexing-overview#vector-embedding). #### SDKs - [Pinecone SDKs overview](https://docs.pinecone.io/reference/pinecone-sdks.md): Browse official Pinecone SDKs for Python, Node.js, Java, and Go, including the version mappings between SDK releases and API versions. ##### Python - [Pinecone Python SDK](https://docs.pinecone.io/reference/sdks/python/overview.md): Install and use the Pinecone SDK for Pinecone Python SDK: auth, typed clients, and API operations. For installation instructions, usage examples, and. - [Reference](https://docs.pinecone.io/reference/sdks/python/reference.md): Reference documentation for the Pinecone Python SDK, including client setup, types, and methods for managing indexes and vector data operations. ##### Node.js - [Pinecone Node.js SDK](https://docs.pinecone.io/reference/sdks/node/overview.md): Install and use the Pinecone Node.js and TypeScript SDK to manage indexes, upsert vectors, run semantic search, and call the Admin and Inference APIs. - [Reference](https://docs.pinecone.io/reference/sdks/node/reference.md): Reference documentation for the Pinecone Node.js SDK, including client setup, types, and methods for managing indexes and vector data operations. ##### Java - [Pinecone Java SDK](https://docs.pinecone.io/reference/sdks/java/overview.md): Install and use the Pinecone Java SDK to manage indexes and namespaces, upsert vectors, run semantic search, and call the Admin and Inference APIs from Java. - [Reference](https://docs.pinecone.io/reference/sdks/java/reference.md): Reference documentation for the Pinecone Java SDK, including client setup, types, and methods for managing indexes and vector data operations. - [OpenTelemetry support](https://docs.pinecone.io/reference/sdks/java/open-telemetry.md): Monitor Pinecone Java SDK operations with OpenTelemetry metrics for client latency, server processing time, and errors via Prometheus. ##### Go - [Pinecone Go SDK](https://docs.pinecone.io/reference/sdks/go/overview.md): Install and use the Pinecone Go SDK to manage indexes and namespaces, upsert vectors, run semantic search, and call the Admin and Inference APIs from Go. - [Reference](https://docs.pinecone.io/reference/sdks/go/reference.md): Reference documentation for the Pinecone Go SDK, including client setup, types, and methods for managing indexes and vector data operations. #### CLI - [CLI quickstart](https://docs.pinecone.io/reference/cli/quickstart.md): Pinecone CLI quickstart for installing pc, authenticating, and managing indexes, vectors, and data imports directly from your terminal. - [CLI command reference](https://docs.pinecone.io/reference/cli/command-reference.md): Complete Pinecone CLI command reference covering syntax, subcommands, flags, help output, and exit codes for auth, index, and project. - [CLI authentication](https://docs.pinecone.io/reference/cli/authentication.md): Authenticate the Pinecone CLI using user login, service accounts, or API keys, including auth priority and Admin API access rules. - [CLI target context](https://docs.pinecone.io/reference/cli/target-context.md): Set the Pinecone CLI target context with pc target to control which organization and project your commands run against, including in CI/CD and JSON mode. #### Tools - [Spark-Pinecone connector](https://docs.pinecone.io/reference/tools/pinecone-spark-connector.md): Pinecone data tools: Use the connector to efficiently create, ingest, and update vector embeddings at scale with Databricks and Pinecone. ### 2024-07 #### APIs - [API reference](https://docs.pinecone.io/reference/api/introduction.md): Pinecone API reference overview for Database, Inference, and Admin endpoints with supported SDKs including Python, Node.js, Java, and Go. - [Authentication](https://docs.pinecone.io/reference/api/authentication.md): Pinecone API authentication guide covering API key generation, SDK client setup, and HTTP header configuration for authorized requests. - [Pinecone API versioning](https://docs.pinecone.io/reference/api/versioning.md): Learn how Pinecone versions its APIs by release date, how long each stable version is supported, and how to set the X-Pinecone-Api-Version header. - [Errors](https://docs.pinecone.io/reference/api/errors.md): Look up the HTTP status codes the Pinecone API returns, what each 2xx success and 4xx or 5xx error means, and where to handle them in production. ##### Database limits - [Pinecone Database limits overview](https://docs.pinecone.io/reference/api/database-limits.md): Reference for Pinecone Database rate, object, operation, and identifier limits, plus known index and serverless limitations. - [Rate limits](https://docs.pinecone.io/reference/api/database-limits/rate-limits.md): Request-per-second, monthly usage, and model throughput limits for Pinecone Database serverless indexes, and the 429 errors returned when you exceed them. - [Object limits](https://docs.pinecone.io/reference/api/database-limits/object-limits.md): Limits on the number and size of Pinecone Database projects, indexes, namespaces, storage, backups, and collections, by plan. - [Operation limits](https://docs.pinecone.io/reference/api/database-limits/operation-limits.md): Fixed limits on Pinecone Database operations, including upsert, update, import, query, fetch, and delete batch sizes and metadata filter expressions. - [Identifier limits](https://docs.pinecone.io/reference/api/database-limits/identifier-limits.md): Maximum length and allowed characters for Pinecone identifiers, including organization, project, index, namespace, and record names. - [Known limitations](https://docs.pinecone.io/reference/api/known-limitations.md): Known limitations and feature restrictions for Pinecone indexes, including upsert consistency, metadata rules, and serverless caveats. #### Database ##### Indexes - [List indexes](https://docs.pinecone.io/reference/api/2024-07/control-plane/list_indexes.md): This operation returns a list of all indexes in a project. - [Create an index](https://docs.pinecone.io/reference/api/2024-07/control-plane/create_index.md): Create an index for vectors created with an external embedding model. For guidance and examples, see [Create an index](https://docs.pinecone.io/guides/index-data/create-an-index). - [Describe an index](https://docs.pinecone.io/reference/api/2024-07/control-plane/describe_index.md): Get a description of an index. - [Delete an index](https://docs.pinecone.io/reference/api/2024-07/control-plane/delete_index.md): Delete an existing index. - [Configure an index](https://docs.pinecone.io/reference/api/2024-07/control-plane/configure_index.md): Configure an existing index. - [Get index stats](https://docs.pinecone.io/reference/api/2024-07/data-plane/describeindexstats.md): The `describe_index_stats` operation returns statistics about the contents of an index, including the vector count per namespace, the number of dimensions, and the index fullness. ##### Vectors - [Upsert vectors](https://docs.pinecone.io/reference/api/2024-07/data-plane/upsert.md): The `upsert` operation writes vectors into a namespace. If a new value is upserted for an existing vector ID, it will overwrite the previous value. - [Search with a vector](https://docs.pinecone.io/reference/api/2024-07/data-plane/query.md): Search a namespace with a query vector or record ID and return the IDs of the most similar records, along with their similarity scores. - [Fetch vectors](https://docs.pinecone.io/reference/api/2024-07/data-plane/fetch.md): The `fetch` operation looks up and returns vectors, by ID, from a single namespace. The returned vectors include the vector data and/or metadata. - [Update a vector](https://docs.pinecone.io/reference/api/2024-07/data-plane/update.md): The `update` operation updates a vector in a namespace. If a value is included, it will overwrite the previous value. If a `set_metadata` is included, the values of the fields specified in it will be added or overwrite the previous value. - [Delete vectors](https://docs.pinecone.io/reference/api/2024-07/data-plane/delete.md): The `delete` operation deletes vectors, by id, from a single namespace. - [List vector IDs](https://docs.pinecone.io/reference/api/2024-07/data-plane/list.md): The `list` operation lists the IDs of vectors in a single namespace of a serverless index. An optional prefix can be passed to limit the results to IDs with a common prefix. ##### Backups - [List collections](https://docs.pinecone.io/reference/api/2024-07/control-plane/list_collections.md): This operation returns a list of all collections in a project. Serverless indexes do not support collections. - [Create a collection](https://docs.pinecone.io/reference/api/2024-07/control-plane/create_collection.md): This operation creates a Pinecone collection. Serverless indexes do not support collections. - [Describe a collection](https://docs.pinecone.io/reference/api/2024-07/control-plane/describe_collection.md): This operation gets a description of a collection. Serverless indexes do not support collections. - [Delete a collection](https://docs.pinecone.io/reference/api/2024-07/control-plane/delete_collection.md): This operation deletes an existing collection. Serverless indexes do not support collections. #### SDKs - [Pinecone SDKs overview](https://docs.pinecone.io/reference/pinecone-sdks.md): Browse official Pinecone SDKs for Python, Node.js, Java, and Go, including the version mappings between SDK releases and API versions. ##### Python - [Pinecone Python SDK](https://docs.pinecone.io/reference/sdks/python/overview.md): Install and use the Pinecone SDK for Pinecone Python SDK: auth, typed clients, and API operations. For installation instructions, usage examples, and. - [Reference](https://docs.pinecone.io/reference/sdks/python/reference.md): Reference documentation for the Pinecone Python SDK, including client setup, types, and methods for managing indexes and vector data operations. ##### Node.js - [Pinecone Node.js SDK](https://docs.pinecone.io/reference/sdks/node/overview.md): Install and use the Pinecone Node.js and TypeScript SDK to manage indexes, upsert vectors, run semantic search, and call the Admin and Inference APIs. - [Reference](https://docs.pinecone.io/reference/sdks/node/reference.md): Reference documentation for the Pinecone Node.js SDK, including client setup, types, and methods for managing indexes and vector data operations. ##### Java - [Pinecone Java SDK](https://docs.pinecone.io/reference/sdks/java/overview.md): Install and use the Pinecone Java SDK to manage indexes and namespaces, upsert vectors, run semantic search, and call the Admin and Inference APIs from Java. - [Reference](https://docs.pinecone.io/reference/sdks/java/reference.md): Reference documentation for the Pinecone Java SDK, including client setup, types, and methods for managing indexes and vector data operations. - [OpenTelemetry support](https://docs.pinecone.io/reference/sdks/java/open-telemetry.md): Monitor Pinecone Java SDK operations with OpenTelemetry metrics for client latency, server processing time, and errors via Prometheus. ##### Go - [Pinecone Go SDK](https://docs.pinecone.io/reference/sdks/go/overview.md): Install and use the Pinecone Go SDK to manage indexes and namespaces, upsert vectors, run semantic search, and call the Admin and Inference APIs from Go. - [Reference](https://docs.pinecone.io/reference/sdks/go/reference.md): Reference documentation for the Pinecone Go SDK, including client setup, types, and methods for managing indexes and vector data operations. #### CLI - [CLI quickstart](https://docs.pinecone.io/reference/cli/quickstart.md): Pinecone CLI quickstart for installing pc, authenticating, and managing indexes, vectors, and data imports directly from your terminal. - [CLI command reference](https://docs.pinecone.io/reference/cli/command-reference.md): Complete Pinecone CLI command reference covering syntax, subcommands, flags, help output, and exit codes for auth, index, and project. - [CLI authentication](https://docs.pinecone.io/reference/cli/authentication.md): Authenticate the Pinecone CLI using user login, service accounts, or API keys, including auth priority and Admin API access rules. - [CLI target context](https://docs.pinecone.io/reference/cli/target-context.md): Set the Pinecone CLI target context with pc target to control which organization and project your commands run against, including in CI/CD and JSON mode. #### Tools - [Spark-Pinecone connector](https://docs.pinecone.io/reference/tools/pinecone-spark-connector.md): Pinecone data tools: Use the connector to efficiently create, ingest, and update vector embeddings at scale with Databricks and Pinecone. ### 2024-04 #### APIs - [API reference](https://docs.pinecone.io/reference/api/introduction.md): Pinecone API reference overview for Database, Inference, and Admin endpoints with supported SDKs including Python, Node.js, Java, and Go. - [Authentication](https://docs.pinecone.io/reference/api/authentication.md): Pinecone API authentication guide covering API key generation, SDK client setup, and HTTP header configuration for authorized requests. - [Pinecone API versioning](https://docs.pinecone.io/reference/api/versioning.md): Learn how Pinecone versions its APIs by release date, how long each stable version is supported, and how to set the X-Pinecone-Api-Version header. - [Errors](https://docs.pinecone.io/reference/api/errors.md): Look up the HTTP status codes the Pinecone API returns, what each 2xx success and 4xx or 5xx error means, and where to handle them in production. ##### Database limits - [Pinecone Database limits overview](https://docs.pinecone.io/reference/api/database-limits.md): Reference for Pinecone Database rate, object, operation, and identifier limits, plus known index and serverless limitations. - [Rate limits](https://docs.pinecone.io/reference/api/database-limits/rate-limits.md): Request-per-second, monthly usage, and model throughput limits for Pinecone Database serverless indexes, and the 429 errors returned when you exceed them. - [Object limits](https://docs.pinecone.io/reference/api/database-limits/object-limits.md): Limits on the number and size of Pinecone Database projects, indexes, namespaces, storage, backups, and collections, by plan. - [Operation limits](https://docs.pinecone.io/reference/api/database-limits/operation-limits.md): Fixed limits on Pinecone Database operations, including upsert, update, import, query, fetch, and delete batch sizes and metadata filter expressions. - [Identifier limits](https://docs.pinecone.io/reference/api/database-limits/identifier-limits.md): Maximum length and allowed characters for Pinecone identifiers, including organization, project, index, namespace, and record names. - [Known limitations](https://docs.pinecone.io/reference/api/known-limitations.md): Known limitations and feature restrictions for Pinecone indexes, including upsert consistency, metadata rules, and serverless caveats. #### Database ##### Indexes - [List indexes](https://docs.pinecone.io/reference/api/2024-04/control-plane/list_indexes.md): This operation returns a list of all indexes in a project. - [Create an index](https://docs.pinecone.io/reference/api/2024-04/control-plane/create_index.md): Create an index for vectors created with an external embedding model. - [Describe an index](https://docs.pinecone.io/reference/api/2024-04/control-plane/describe_index.md): Get a description of an index. - [Delete an index](https://docs.pinecone.io/reference/api/2024-04/control-plane/delete_index.md): This operation deletes an existing index. - [Configure an index](https://docs.pinecone.io/reference/api/2024-04/control-plane/configure_index.md): This operation configures the pod size and number of replicas for a pod-based index. - [Get index stats](https://docs.pinecone.io/reference/api/2024-04/data-plane/describeindexstats.md): The `describe_index_stats` operation returns statistics about the contents of an index, including the vector count per namespace, the number of dimensions, and the index fullness. ##### Vectors - [Upsert vectors](https://docs.pinecone.io/reference/api/2024-04/data-plane/upsert.md): The `upsert` operation writes vectors into a namespace. If a new value is upserted for an existing vector ID, it will overwrite the previous value. - [Search with a vector](https://docs.pinecone.io/reference/api/2024-04/data-plane/query.md): The `query` operation searches a namespace, using a query vector. It retrieves the ids of the most similar items in a namespace, along with their similarity scores. - [Fetch vectors](https://docs.pinecone.io/reference/api/2024-04/data-plane/fetch.md): The `fetch` operation looks up and returns vectors, by ID, from a single namespace. The returned vectors include the vector data and/or metadata. For on-demand indexes, since vector values are retrieved from object storage, fetch operations may have increased latency. If you only need metadata or ID… - [Update a vector](https://docs.pinecone.io/reference/api/2024-04/data-plane/update.md): The `update` operation updates a vector in a namespace. If a value is included, it will overwrite the previous value. If a `set_metadata` is included, the values of the fields specified in it will be added or overwrite the previous value. - [Delete vectors](https://docs.pinecone.io/reference/api/2024-04/data-plane/delete.md): The `delete` operation deletes vectors, by id, from a single namespace. - [List vector IDs](https://docs.pinecone.io/reference/api/2024-04/data-plane/list.md): The `list` operation lists the IDs of vectors in a single namespace of a serverless index. An optional prefix can be passed to limit the results to IDs with a common prefix. ##### Backups - [List collections](https://docs.pinecone.io/reference/api/2024-04/control-plane/list_collections.md): This operation returns a list of all collections in a project. - [Create a collection](https://docs.pinecone.io/reference/api/2024-04/control-plane/create_collection.md): This operation creates a Pinecone collection. - [Describe a collection](https://docs.pinecone.io/reference/api/2024-04/control-plane/describe_collection.md): This operation gets a description of a collection. - [Delete a collection](https://docs.pinecone.io/reference/api/2024-04/control-plane/delete_collection.md): This operation deletes an existing collection. #### SDKs - [Pinecone SDKs overview](https://docs.pinecone.io/reference/pinecone-sdks.md): Browse official Pinecone SDKs for Python, Node.js, Java, and Go, including the version mappings between SDK releases and API versions. ##### Python - [Pinecone Python SDK](https://docs.pinecone.io/reference/sdks/python/overview.md): Install and use the Pinecone SDK for Pinecone Python SDK: auth, typed clients, and API operations. For installation instructions, usage examples, and. - [Reference](https://docs.pinecone.io/reference/sdks/python/reference.md): Reference documentation for the Pinecone Python SDK, including client setup, types, and methods for managing indexes and vector data operations. ##### Node.js - [Pinecone Node.js SDK](https://docs.pinecone.io/reference/sdks/node/overview.md): Install and use the Pinecone Node.js and TypeScript SDK to manage indexes, upsert vectors, run semantic search, and call the Admin and Inference APIs. - [Reference](https://docs.pinecone.io/reference/sdks/node/reference.md): Reference documentation for the Pinecone Node.js SDK, including client setup, types, and methods for managing indexes and vector data operations. ##### Java - [Pinecone Java SDK](https://docs.pinecone.io/reference/sdks/java/overview.md): Install and use the Pinecone Java SDK to manage indexes and namespaces, upsert vectors, run semantic search, and call the Admin and Inference APIs from Java. - [Reference](https://docs.pinecone.io/reference/sdks/java/reference.md): Reference documentation for the Pinecone Java SDK, including client setup, types, and methods for managing indexes and vector data operations. - [OpenTelemetry support](https://docs.pinecone.io/reference/sdks/java/open-telemetry.md): Monitor Pinecone Java SDK operations with OpenTelemetry metrics for client latency, server processing time, and errors via Prometheus. ##### Go - [Pinecone Go SDK](https://docs.pinecone.io/reference/sdks/go/overview.md): Install and use the Pinecone Go SDK to manage indexes and namespaces, upsert vectors, run semantic search, and call the Admin and Inference APIs from Go. - [Reference](https://docs.pinecone.io/reference/sdks/go/reference.md): Reference documentation for the Pinecone Go SDK, including client setup, types, and methods for managing indexes and vector data operations. #### CLI - [CLI quickstart](https://docs.pinecone.io/reference/cli/quickstart.md): Pinecone CLI quickstart for installing pc, authenticating, and managing indexes, vectors, and data imports directly from your terminal. - [CLI command reference](https://docs.pinecone.io/reference/cli/command-reference.md): Complete Pinecone CLI command reference covering syntax, subcommands, flags, help output, and exit codes for auth, index, and project. - [CLI authentication](https://docs.pinecone.io/reference/cli/authentication.md): Authenticate the Pinecone CLI using user login, service accounts, or API keys, including auth priority and Admin API access rules. - [CLI target context](https://docs.pinecone.io/reference/cli/target-context.md): Set the Pinecone CLI target context with pc target to control which organization and project your commands run against, including in CI/CD and JSON mode. #### Tools - [Spark-Pinecone connector](https://docs.pinecone.io/reference/tools/pinecone-spark-connector.md): Pinecone data tools: Use the connector to efficiently create, ingest, and update vector embeddings at scale with Databricks and Pinecone. ## OpenAPI Specs - [db_control_2026-07.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2026-07/db_control_2026-07.oas.yaml) - [db_data_2026-07.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2026-07/db_data_2026-07.oas.yaml) - [inference_2026-07.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2026-07/inference_2026-07.oas.yaml) - [admin_2026-07.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2026-07/admin_2026-07.oas.yaml) - [db_control_2026-04.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2026-04/db_control_2026-04.oas.yaml) - [db_data_2026-04.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2026-04/db_data_2026-04.oas.yaml) - [inference_2026-04.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2026-04/inference_2026-04.oas.yaml) - [admin_2026-04.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2026-04/admin_2026-04.oas.yaml) - [oauth_2026-04.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2026-04/oauth_2026-04.oas.yaml) - [db_control_2025-10.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2025-10/db_control_2025-10.oas.yaml) - [db_data_2025-10.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2025-10/db_data_2025-10.oas.yaml) - [inference_2025-10.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2025-10/inference_2025-10.oas.yaml) - [admin_2025-10.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2025-10/admin_2025-10.oas.yaml) - [oauth_2025-10.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2025-10/oauth_2025-10.oas.yaml) - [db_control_2025-04.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2025-04/db_control_2025-04.oas.yaml) - [db_data_2025-04.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2025-04/db_data_2025-04.oas.yaml) - [inference_2025-04.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2025-04/inference_2025-04.oas.yaml) - [admin_2025-04.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2025-04/admin_2025-04.oas.yaml) - [oauth_2025-04.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2025-04/oauth_2025-04.oas.yaml) - [db_control_2025-01.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2025-01/db_control_2025-01.oas.yaml) - [db_data_2025-01.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2025-01/db_data_2025-01.oas.yaml) - [inference_2025-01.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2025-01/inference_2025-01.oas.yaml) - [db_control_2024-10.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2024-10/db_control_2024-10.oas.yaml) - [db_data_2024-10.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2024-10/db_data_2024-10.oas.yaml) - [inference_2024-10.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2024-10/inference_2024-10.oas.yaml) - [control_2024-07.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2024-07/control_2024-07.oas.yaml) - [data_2024-07.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2024-07/data_2024-07.oas.yaml) - [control_2024-04.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2024-04/control_2024-04.oas.yaml) - [data_2024-04.oas](https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2024-04/data_2024-04.oas.yaml)