Deploy and Host pg_pinecone on Railway

pg_pinecone is an open-source Postgres extension for vector & full-text search on the data you already store, built on the engine Pinecone runs at scale. You use the same SQL as pgvector. A filter such as a tenant applies during the search, and the rows stay in Postgres. When a table needs more scale, send its search to Pinecone as a remote backend. Your queries stay the same.

About Hosting pg_pinecone

This template deploys PostgreSQL 18 with pg_pinecone installed. Railway keeps the data on a volume and gives you a connection URL. The railway database already has the extensions enabled.

Use DATABASE_URL from other services in the project. Use DATABASE_PUBLIC_URL from your own computer.

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]');

SELECT pinecone.create_index('items', 'embedding');

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

That search runs inside Postgres.

A Pinecone API key adds a few optional tools. Turn them on one at a time:

A remote backend, when you need more scale
embed(), to turn text into vectors from SQL
Keyword search, and search that combines keywords with vectors
rerank(), to put the best results first

Common Use Cases

Find the records behind a support assistant, a recommendation, or an agent that remembers past work
Search by meaning, by keyword, or by both in one query
Limit a search to one tenant, user, or category while still filling the result list
Keep embeddings in Postgres, and send search to a remote backend when a table needs more scale

Dependencies for pg_pinecone Hosting

The image includes PostgreSQL 18 and pg_pinecone. For the product itself, refer to more information here:

Why Deploy pg_pinecone on Railway

You get search inside Postgres from one deploy. Connect with the URL Railway gives you, query with the SQL you already use, and add Pinecone as a remote backend when you need more scale.