December 2023


  • The free Starter plan now supports up to 100 namespaces. Namespaces let you partition vectors within an index to speed up queries or comply with multi-tenancy requirements.

November 2023


  • The new Pinecone AWS Reference Architecture is an open-source, distributed system that performs vector-database-enabled semantic search over Postgres records. You can use it as a learning resource or as a starting point for high-scale use cases.


  • Canopy is a new open-source Retrieval Augmented Generation (RAG) framework and context engine built on top of Pinecone. It enables you to start chatting with your documents or text data with a few simple commands.
    The latest version of the Canopy SDK (v0.2.0) adds support for OpenAI SDK v1.2.3. See the release notes in GitHub for more details.


  • Pinecone is now registered to collect Value Added Tax (VAT) or Goods and Services Tax (GST) for accounts based in various global regions. If applicable, add your VAT or GST number to your account under Settings > Billing.

October 2023




  • The latest version of our Node SDK is v1.1.2. See the release notes in GitHub for more details.


  • The Index Browser is now available in the console. This allows you to preview, query, and filter by metadata directly from the console. The Index Browser can be found within the index detail page.
  • We’re improved the design of our metrics page to include new charts for record and error count plus additional latencies (p90, p99) to help triage and understand issues.


  • Knowledge Base for Amazon Bedrock is now available in Private Preview. Integrate your enterprise data via retrieval augmented generation (RAG) when building search and GenAI applications. Learn more.
  • Pinecone Sink Connector for Confluent is now available in Public Preview. Gain access to data streams from across your business to build a real-time knowledge base for your AI applications. Learn more.



  • Pinecone is now HIPAA compliant across all of our cloud providers (AWS, Azure, and GCP).

September 11, 2023

Pinecone Azure support via the eastus-azure region is now generally available (GA).

August 14, 2023

Pinecone now supports deploying projects to Azure using the new eastus-azure region. This is a public preview environment, so test thoroughly before deploying to production.

June 21, 2023

The new gcp-starter region is now in public preview. This region has distinct limitations from other Starter Plan regions. gcp-starter is the default region for some new users.

April 26, 2023

Indexes in the starter plan now support approximately 100,000 1536-dimensional embeddings with metadata. Capacity is proportional for other dimensionalities.

April 3, 2023

Pinecone now supports new US and EU cloud regions.

March 21, 2023

Pinecone now supports SSO for Enterprise dedicated customers. Contact us at to set up your integration.

March 1, 2023

Pinecone now supports 40kb of metadata per vector.

February 22, 2023

Sparse-dense embeddings are now in Public Preview.

Pinecone now supports vectors with sparse and dense values. To use sparse-dense embeddings in Python, upgrade to Python client version 2.2.0.

Pinecone Python client version 2.2.0 is available

Python client version 2.2.0 with support for sparse-dense embeddings is now available on GitHub and PYPI.

February 15, 2023

New Node.js client is now available in public preview

You can now try out our new Node.js client for Pinecone.

February 14, 2023

New usage reports in the Pinecone console

You can now monitor your current and projected Pinecone usage with the Usage dashboard.

January 31, 2023

Pinecone is now available in AWS Marketplace

You can now sign up for Pinecone billing through Amazon Web Services Marketplace.

January 3, 2023

Pinecone Python client version 2.1.0 is now available on GitHub.

The latest release of the Python client makes the following changes:

  • Fixes “Connection Reset by peer” error after long idle periods
  • Adds typing and explicit names for arguments in all client operations
  • Adds docstrings to all client operations
  • Adds Support for batch upserts by passing batch_size to the upsert method
  • Improves gRPC query results parsing performance