# Pinecone Docs: Pinecone Database Guides

> Official Pinecone documentation for the vector database, Assistant, inference APIs, SDKs, and building production search and AI applications.

## Guides

### Get started

- [Pinecone documentation](https://docs.pinecone.io/guides/get-started/overview.md): Pinecone is the vector database for AI agents and applications, built for semantic search, knowledge retrieval, and long-term memory at scale.

#### Quickstart

- [Pinecone quickstart](https://docs.pinecone.io/guides/get-started/quickstart.md): Get started with Pinecone in minutes. Pick the path that matches what you're searching for and run your first search.
- [Ingest your own files](https://docs.pinecone.io/guides/get-started/quickstart/ingest-files.md): Turn a folder of documents into a searchable index: extract text, chunk it, embed the chunks, and upsert.
- [Bring your own vectors](https://docs.pinecone.io/guides/get-started/quickstart/bring-your-own-vectors.md): Create an index with a dense-vector field, upsert embeddings you already have, and run semantic search.
- [Try full-text search](https://docs.pinecone.io/guides/get-started/quickstart/full-text-search.md): Create an index, load documents, and run your first full-text (keyword) search in about five minutes.

### Core concepts

- [Pinecone key terms](https://docs.pinecone.io/guides/core-concepts/key-terms.md): The key terms and objects in Pinecone and how they relate to each other.
- [Architecture](https://docs.pinecone.io/guides/core-concepts/architecture.md): Learn how Pinecone is built, from organizations, projects, indexes, and namespaces down to the infrastructure that stores and serves your data.

### Index data

- [Index data overview](https://docs.pinecone.io/guides/index-data/indexing-overview.md): Learn how indexing works in Pinecone: serverless indexes, schemas, namespaces, integrated embedding, and metadata filtering.
- [Data modeling](https://docs.pinecone.io/guides/index-data/data-modeling.md): Model your data in Pinecone using documents with dense_vector, sparse_vector, full-text string, and metadata fields for efficient retrieval.
- [Dedicated read nodes](https://docs.pinecone.io/guides/index-data/dedicated-read-nodes.md): Dedicated read nodes use provisioned hardware for read operations, providing predictable, low-latency performance at high query volumes.
- [Adopt the Documents API](https://docs.pinecone.io/guides/index-data/adopt-the-documents-api.md): Learn what changes in API version 2026-07, whether your existing code is affected, and how to move to schema-based indexes.

#### Create and configure

- [Create an index](https://docs.pinecone.io/guides/index-data/create-an-index.md): Create a Pinecone serverless index for full-text (BM25), semantic (dense vector), sparse-vector, or hybrid search with a document schema.
- [Configure metadata indexing](https://docs.pinecone.io/guides/index-data/configure-metadata-indexing.md): Limit metadata indexing in Pinecone to the fields you filter on, to keep index building and query execution fast.

#### Data ingestion

- [Data ingestion overview](https://docs.pinecone.io/guides/index-data/data-ingestion-overview.md): Compare data ingestion options in Pinecone: bulk import from object storage, upsert operations, and hosted embedding via the Inference API.
- [Upsert records](https://docs.pinecone.io/guides/index-data/upsert-data.md): Upsert dense, sparse, and text records into Pinecone indexes, batch upserts for higher throughput, and partition data with namespaces.
- [Import records](https://docs.pinecone.io/guides/index-data/import-data.md): Import large datasets efficiently from Amazon S3, Google Cloud Storage, or Azure Blob Storage into Pinecone serverless indexes using object storage.
- [Migrate from pgvector](https://docs.pinecone.io/guides/index-data/migrate-from-pgvector.md): Migrate vector data from pgvector to Pinecone Database, validate search results, synchronize incremental changes, and cut over application traffic.
- [Check data freshness](https://docs.pinecone.io/guides/index-data/check-data-freshness.md): Check data freshness in Pinecone serverless indexes using log sequence numbers (LSNs) and vector counts to verify recent upserts and deletes.

#### Multitenancy

- [Design for multitenancy](https://docs.pinecone.io/guides/index-data/design-for-multitenancy.md): Design multitenancy in Pinecone by choosing between namespace-per-tenant isolation and metadata filtering, with their cost and performance tradeoffs.
- [Implement multitenancy](https://docs.pinecone.io/guides/index-data/implement-multitenancy.md): Implement multitenancy in Pinecone with one namespace per tenant on a serverless index to isolate customer data for SaaS RAG or semantic search apps.

### Search

- [Search overview](https://docs.pinecone.io/guides/search/search-overview.md): Compare Pinecone search types and choose the right retrieval approach: full-text (BM25), semantic (dense vector), sparse-vector, and hybrid.
- [Semantic search](https://docs.pinecone.io/guides/search/semantic-search.md): Search a Pinecone index of dense vectors to find semantically similar records using text or vector queries, top_k results, and nearest neighbor lookup.
- [Sparse-vector search](https://docs.pinecone.io/guides/search/lexical-search.md): Run sparse-vector search in Pinecone with custom sparse encoders like pinecone-sparse-english-v0 for token-weighted keyword retrieval.
- [Filter by metadata](https://docs.pinecone.io/guides/search/filter-by-metadata.md): Narrow Pinecone search results by adding metadata filter expressions to your query, using operators like $eq, $in, $gt, and $and for precise retrieval.
- [Rerank results](https://docs.pinecone.io/guides/search/rerank-results.md): Improve retrieval quality by reranking initial search results with a hosted or external model to surface the most relevant matches for RAG.

#### Full-text search

- [Full-text search overview](https://docs.pinecone.io/guides/search/full-text-search.md): Upsert and search typed JSON documents in Pinecone with BM25 scoring, Lucene query syntax, dense and sparse vector ranking, and metadata filters.
- [Full-text search query syntax](https://docs.pinecone.io/guides/search/full-text-search/query-syntax.md): Write Pinecone full-text search queries with Lucene query_string syntax, including boolean, phrase, prefix, boosting, and fuzzy operators.
- [Full-text search text processing](https://docs.pinecone.io/guides/search/full-text-search/text-processing.md): Control how Pinecone full-text search tokenizes and analyzes text, including tokens and analyzers, stemming, language options, and substring (n-gram) matching.

#### Hybrid search

- [Hybrid search overview](https://docs.pinecone.io/guides/search/hybrid-search.md): Combine keyword and semantic retrieval in Pinecone with a text-match filter on a dense search, or by fusing separate searches with reciprocal rank fusion.
- [Run hybrid search on a single index](https://docs.pinecone.io/guides/search/hybrid-search/single-index.md): Run hybrid search on one Pinecone index storing a dense and a sparse vector per record, weighting the two signals client-side with an alpha value.
- [Run hybrid search on separate indexes](https://docs.pinecone.io/guides/search/hybrid-search/separate-indexes.md): Store dense and sparse vectors in two Pinecone indexes linked by ID, query each, and merge the results client-side with reciprocal rank fusion.
- [Reciprocal rank fusion](https://docs.pinecone.io/guides/search/reciprocal-rank-fusion.md): Combine results from separate Pinecone searches into a single ranking with reciprocal rank fusion (RRF), a client-side method that fuses rankings, not scores.

### Optimize

- [Increase search relevance](https://docs.pinecone.io/guides/optimize/increase-relevance.md): Improve Pinecone search quality with reranking models, metadata filtering, and hybrid search that combines full-text and vector retrieval for RAG.
- [Increase throughput](https://docs.pinecone.io/guides/optimize/increase-throughput.md): Increase Pinecone throughput with bulk import from object storage, batch upserts, parallel requests, and the Python gRPC SDK for faster ingestion.
- [Decrease latency](https://docs.pinecone.io/guides/optimize/decrease-latency.md): Reduce query and upsert latency in Pinecone using namespaces, metadata filters, targeting indexes by host, and regional colocation strategies.
- [Save on Pinecone costs](https://docs.pinecone.io/guides/optimize/save-on-costs.md): Save on Pinecone costs by using bulk import over upsert, namespaces for multitenancy, and query patterns that reduce read unit consumption.
- [Test Pinecone at scale](https://docs.pinecone.io/guides/optimize/test-at-scale.md): Benchmark Pinecone at production scale by importing 10M vectors and measuring semantic search throughput, query latency, and costs.

### Manage data

- [Target an index](https://docs.pinecone.io/guides/manage-data/target-an-index.md): Target a Pinecone index by host URL (recommended for production) or by name for data operations like upsert, query, and fetch across SDKs.
- [Manage serverless indexes](https://docs.pinecone.io/guides/manage-data/manage-indexes.md): List, describe, configure, and delete serverless indexes in Pinecone, including tags, deletion protection, and metadata index configuration.
- [Manage namespaces](https://docs.pinecone.io/guides/manage-data/manage-namespaces.md): Create, describe, list, and delete namespaces in Pinecone serverless indexes, including defining filterable metadata fields and schemas ahead of upsert.
- [Update data](https://docs.pinecone.io/guides/manage-data/update-data.md): Patch fields on Pinecone documents by ID, update record metadata and vector values by ID, or update metadata across documents and records with a filter.
- [Delete data](https://docs.pinecone.io/guides/manage-data/delete-data.md): Delete Pinecone documents or records from a namespace by ID or metadata filter, or delete every document or record the namespace holds.
- [Fetch data](https://docs.pinecone.io/guides/manage-data/fetch-data.md): Retrieve Pinecone documents or records from a namespace by ID or metadata filter to inspect their fields, vector values, and metadata.
- [List IDs](https://docs.pinecone.io/guides/manage-data/list-record-ids.md): List the IDs of Pinecone documents or records in a namespace of a serverless index, filter them by ID prefix, and paginate through the results.

#### Manage backups

- [Backups overview](https://docs.pinecone.io/guides/manage-data/backups-overview.md): Learn how serverless index backups work in Pinecone, including scheduled backups, retention policies, and use cases for restoring or copying data.
- [Back up an index](https://docs.pinecone.io/guides/manage-data/back-up-an-index.md): Create backups of serverless indexes to protect data, copy indexes, or experiment with configurations using the Pinecone SDK, API, or console.
- [Restore an index](https://docs.pinecone.io/guides/manage-data/restore-an-index.md): Restore a Pinecone serverless index from a backup, change the index name, tags, or deletion protection, and preserve embedding model configuration.

### Manage cost

- [Understanding Pinecone cost](https://docs.pinecone.io/guides/manage-cost/understanding-cost.md): Understand how costs are incurred in Pinecone, including read units (RUs), write units (WUs), storage, egress, and embedding.
- [Manage cost](https://docs.pinecone.io/guides/manage-cost/manage-cost.md): Reduce Pinecone spend with strategies like spend alerts, ID-prefix listing, multitenant namespaces, prepaid credits, and support cost optimization help.
- [Monitor usage and costs](https://docs.pinecone.io/guides/manage-cost/monitor-usage-and-costs.md): Monitor Pinecone usage and costs at the organization, index, and operation level by tracking read units, write units, and storage consumption.

### Move to production

- [Production checklist](https://docs.pinecone.io/guides/production/production-checklist.md): Prepare Pinecone indexes for production with best practices for project structure, security, scaling, API keys, and reliability across your workloads.
- [Bring Your Own Cloud (BYOC)](https://docs.pinecone.io/guides/production/bring-your-own-cloud.md): Deploy Pinecone BYOC in your own AWS, GCP, or Azure account for data sovereignty, network isolation, and regional data residency requirements.
- [Error handling](https://docs.pinecone.io/guides/production/error-handling.md): Handle Pinecone API errors with retry logic, exponential backoff, and best practices for 4xx client errors, 5xx server errors, and rate limit responses.
- [Monitor performance](https://docs.pinecone.io/guides/production/monitoring.md): Monitor Pinecone index performance metrics (query latency, throughput, and errors) in the Pinecone console or via Prometheus and Datadog.
- [CI/CD with Pinecone Local and GitHub Actions](https://docs.pinecone.io/guides/production/automated-testing.md): Build a GitHub Actions CI/CD workflow with Pinecone Local to run automated integration tests against an in-memory emulator without touching production.

#### Enforce security

- [Security overview](https://docs.pinecone.io/guides/production/security-overview.md): Overview of Pinecone security features for production: API keys, SSO, service accounts, audit logs, CMEK encryption, backups, and Private Endpoints.
- [Manage roles and access](https://docs.pinecone.io/guides/production/manage-rbac.md): Assign and manage roles for users, service accounts, and API keys using the Pinecone console or the Admin API.
- [Configure SSO with Okta](https://docs.pinecone.io/guides/production/configure-single-sign-on/okta.md): Set up SAML single sign-on between Pinecone and Okta so your organization members can log in with corporate credentials.
- [Manage roles with Okta](https://docs.pinecone.io/guides/production/configure-single-sign-on/okta-role-management.md): Automatically assign Pinecone organization and project roles from SAML attributes with Okta.
- [SCIM provisioning with Okta](https://docs.pinecone.io/guides/production/configure-single-sign-on/okta-scim-provisioning.md): Automatically provision members and roles from Okta to Pinecone over SCIM.
- [Configure customer-managed encryption keys](https://docs.pinecone.io/guides/production/configure-cmek.md): Set up customer-managed encryption keys (CMEK) with AWS KMS to encrypt Pinecone data with keys you control, using IAM roles and key policies.
- [Configure Private Endpoints](https://docs.pinecone.io/guides/production/configure-private-endpoints.md): Configure Pinecone Private Endpoints with AWS PrivateLink or Azure Private Link to keep index traffic off the public internet and secure VPCs.
- [Data deletion on Pinecone](https://docs.pinecone.io/guides/production/data-deletion.md): Learn how Pinecone permanently deletes customer data, including soft deletion, the 90-day retention window, and secure erasure of records and indexes.
- [Configure audit logs](https://docs.pinecone.io/guides/production/configure-audit-logs.md): Enable Pinecone audit logging to an Amazon S3 bucket to track user, service account, and API actions for compliance, security review, and WORM retention.

### Admin

#### Manage billing

- [Upgrade your plan](https://docs.pinecone.io/guides/organizations/manage-billing/upgrade-billing-plan.md): Upgrade to a paid Pinecone plan for higher limits, backups, private endpoints, audit logs, and access to the Builder, Standard, or Enterprise tiers.
- [Change your payment method](https://docs.pinecone.io/guides/organizations/manage-billing/change-payment-method.md): Update your Pinecone organization payment method in the console, including credit card details, billing address, and payment preferences.
- [Account deactivation for non-payment](https://docs.pinecone.io/guides/organizations/manage-billing/non-payment-account-deactivation.md): Learn what happens when a Pinecone account is deactivated for non-payment: 30-day data retention, permanent deletion, and how to reactivate.
- [Downgrade your plan](https://docs.pinecone.io/guides/organizations/manage-billing/downgrade-billing-plan.md): Downgrade your Pinecone organization from a paid plan to the free Starter plan, including plan requirements, index limits, and billing impact.
- [Download a usage report](https://docs.pinecone.io/guides/organizations/manage-billing/download-usage-report.md): Download detailed Pinecone usage and cost reports from the console, including index consumption, storage metrics, and per-project spend breakdowns.
- [Access your invoices](https://docs.pinecone.io/guides/organizations/manage-billing/access-your-invoices.md): View and download your Pinecone organization billing invoices in the console, including invoice history, receipts, and payment records.
- [Pinecone Standard plan trial](https://docs.pinecone.io/guides/organizations/manage-billing/standard-trial.md): Evaluate the Pinecone Standard plan with $300 in credits over 21 days, including bulk import, backup and restore, RBAC, and higher scale limits.

#### Manage organizations

- [Understanding organizations](https://docs.pinecone.io/guides/organizations/understanding-organizations.md): Learn how Pinecone organizations group projects, share billing, and use organization roles to control member permissions and access to resources.
- [Manage organization members](https://docs.pinecone.io/guides/organizations/manage-organization-members.md): Add, invite, and manage members in your Pinecone organization, including assigning organization roles, changing permissions, and removing users.
- [Manage service accounts at the organization-level](https://docs.pinecone.io/guides/organizations/manage-service-accounts.md): Create and manage service accounts at the organization level in Pinecone for programmatic Admin API access, including client secrets and role assignment.

#### Manage projects

- [Understanding projects](https://docs.pinecone.io/guides/projects/understanding-projects.md): Learn how Pinecone projects organize indexes, cloud environments, API keys, and members, including project roles and per-role permission summaries.
- [Create a project](https://docs.pinecone.io/guides/projects/create-a-project.md): Create a new Pinecone project in your organization using the console or Admin API, including project name, tags, and customer-managed encryption keys (CMEK).
- [Manage projects](https://docs.pinecone.io/guides/projects/manage-projects.md): View project details, rename projects, and delete projects in your Pinecone organization using the console or Admin API with owner permissions.
- [Manage project members](https://docs.pinecone.io/guides/projects/manage-project-members.md): Add, remove, and update Pinecone project members using role-based access control (RBAC) to manage permissions and project owner roles.
- [Manage API keys](https://docs.pinecone.io/guides/projects/manage-api-keys.md): Create, view, update, and delete Pinecone API keys with custom permissions per project, including scoped roles and data plane access controls.
- [Manage service accounts at the project-level](https://docs.pinecone.io/guides/projects/manage-service-accounts.md): Add service accounts to a Pinecone project and assign project roles to enable programmatic API access for automated workflows and CI pipelines.

### Operations

- [Local development with Pinecone Local](https://docs.pinecone.io/guides/operations/local-development.md): Run Pinecone Local, an in-memory Docker emulator, to develop and test apps offline without an account or usage fees.

#### Integrate with cloud storage

- [Integrate with Amazon S3](https://docs.pinecone.io/guides/operations/integrations/integrate-with-amazon-s3.md): Set up a Pinecone storage integration with an Amazon S3 bucket using an IAM role to bulk import data into indexes and export audit logs.
- [Integrate with Google Cloud Storage](https://docs.pinecone.io/guides/operations/integrations/integrate-with-google-cloud-storage.md): Set up a Pinecone storage integration with a Google Cloud Storage bucket using a service account key to bulk import data into your indexes.
- [Integrate with Azure Blob Storage](https://docs.pinecone.io/guides/operations/integrations/integrate-with-azure-blob-storage.md): Set up a Pinecone storage integration with an Azure Blob Storage container using a service principal to bulk import data into your indexes.
- [Manage storage integrations](https://docs.pinecone.io/guides/operations/integrations/manage-storage-integrations.md): Update or delete existing Amazon S3, Google Cloud Storage, and Azure Blob storage integrations for your Pinecone project in the console.

#### Integrate with AI agents

- [Use the Pinecone MCP server](https://docs.pinecone.io/guides/operations/mcp-server.md): Connect AI agents to Pinecone through the MCP server to search docs, manage indexes, and query data from Claude, Cursor, Antigravity, or Claude Code.
- [Build a knowledge retrieval agent](https://docs.pinecone.io/guides/operations/build-a-knowledge-agent.md): Build an AI agent that uses Pinecone to retrieve knowledge and answer questions accurately, with Pinecone as a tool inside the agent.

### Using pods

- [Understanding pod-based indexes](https://docs.pinecone.io/guides/indexes/pods/understanding-pod-based-indexes.md): Understand Pinecone pod-based indexes, including pod types and sizing. Legacy: pod indexes are unavailable to new customers; use serverless for new projects.
- [Migrate a pod-based index to serverless](https://docs.pinecone.io/guides/indexes/pods/migrate-a-pod-based-index-to-serverless.md): Migrate a Pinecone pod-based index to serverless for automatic scaling, better performance, and usage-based pricing with no minimum spend commitment.
- [Choose a pod type and size](https://docs.pinecone.io/guides/indexes/pods/choose-a-pod-type-and-size.md): Choose a Pinecone pod type and size (s1, p1, p2). Legacy guide: pods are unavailable to new customers as of August 2025; serverless needs no planning.
- [Create a pod-based index](https://docs.pinecone.io/guides/indexes/pods/create-a-pod-based-index.md): Create a Pinecone pod-based index. Legacy guide: new customers cannot create pod indexes as of August 2025; use serverless index creation instead.
- [Manage pod-based indexes](https://docs.pinecone.io/guides/indexes/pods/manage-pod-based-indexes.md): Manage Pinecone pod-based indexes. Legacy guide: pod indexes are unavailable to new customers as of August 2025; serverless is recommended for new projects.
- [Scale pod-based indexes](https://docs.pinecone.io/guides/indexes/pods/scale-pod-based-indexes.md): Scale Pinecone pod-based indexes by adding pods or replicas. Legacy guide: pod indexes are unavailable to new customers; serverless scales automatically.

#### Back up and restore

- [Understanding collections](https://docs.pinecone.io/guides/indexes/pods/understanding-collections.md): Legacy documentation for Pinecone collections, a pod-only feature for creating static index snapshots. Collections are not available for serverless indexes.
- [Back up a pod-based index](https://docs.pinecone.io/guides/indexes/pods/back-up-a-pod-based-index.md): Legacy guide for backing up Pinecone pod-based indexes using collections. Collections are a pod-only feature not available for serverless indexes.
- [Restore a pod-based index](https://docs.pinecone.io/guides/indexes/pods/restore-a-pod-based-index.md): Legacy guide for restoring Pinecone pod-based indexes from collections. Pod indexes are no longer available to new customers as of August 2025.