An open-source PostgreSQL extension that brings Pinecone's vector search into the Postgres database you already run. Keep your tables and your pgvector queries, and choose an engine per table.

• Three engines behind one index: pgvector, native (the default), and remote. Switch a table between them without changing a query.
• Filtered search inside Postgres: the native engine applies a filter such as a tenant ID during the search, with no account or network access.
• Scale out when you need to: the remote engine moves a table's search to a Pinecone serverless index, and Postgres keeps every row.
• Full-text search: keep a Pinecone index for full-text search in sync with a table and run BM25, vector, or hybrid searches from SQL.
• pgvector compatible: index existing vector columns as they are.

Every switch can be reversed. The pg_pinecone docs cover how the engines compare and how to switch between them.

Requirements: PostgreSQL 17 or 18, superuser access, and pgvector installed on the server.

Install it one of two ways:

• Prebuilt release: download the archive for your platform and Postgres version from the releases page and copy its files into your Postgres installation, as step 1 of the quickstart shows.
• Docker: pineconeteam/pg_pinecone is the pgvector/pgvector image with pg_pinecone added, one tag per Postgres major: docker run -d -e POSTGRES_PASSWORD=secret pineconeteam/pg_pinecone:0.11.0-pg17 (add -c shared_preload_libraries=pg_pinecone for the remote engine).

Then create the extensions and index a vector column:

CREATE EXTENSION vector;
CREATE EXTENSION pg_pinecone;

CREATE TABLE items (id bigint PRIMARY KEY, embedding vector(3));
INSERT INTO items VALUES (1, '[1,2,3]'), (2, '[4,5,6]'), (3, '[7,8,9]');

-- Builds a native index. No API key or network access needed.
SELECT pinecone.create_index('items', 'embedding');

SELECT id FROM items ORDER BY embedding <=> '[1,2,4]' LIMIT 2;

For a full walkthrough on a sample table, including semantic search with embeddings, see the quickstart in the pg_pinecone docs.

pg_pinecone is built with pgrx. You need a Rust toolchain and the headers of the Postgres you're building for (pg_config on your PATH, or pass its path to --pg-config).

git clone https://github.com/pinecone-io/pg_pinecone.git
cd pg_pinecone/pg_pinecone
cargo install cargo-pgrx --version 0.19.2 --locked
cargo pgrx init --pg17 "$(which pg_config)"   # use --pg18 for PostgreSQL 18
cargo pgrx install --release                  # builds and installs into that Postgres

cargo pgrx install writes the extension into the Postgres pg_config points at; then CREATE EXTENSION vector; CREATE EXTENSION pg_pinecone; as above. On x86_64 the build targets your own CPU, so it runs anywhere you build it. For running the tests, see CONTRIBUTING.md.

The pg_pinecone docs on docs.pinecone.io cover installation, the storage engines, switching engines, and full-text search.

In this repository:

• SQL reference: every function, setting, and error message
• Operator runbook: monitoring, upgrades, and maintenance
• Disaster recovery: restoring a remote table
• Changelog

• Questions and feedback: the Pinecone Discord community
• Bugs and feature requests: GitHub issues
• Security issues: see SECURITY.md

Start with an issue. See CONTRIBUTING.md for how proposals and pull requests work.

Apache License 2.0