Overview

TheoDB is a PostgreSQL 17 distribution that puts AI — embeddings, generation, ranking, natural-language queries — and vector search into the database as plain SQL functions. It is not a fork or a new engine: it composes upstream PostgreSQL with a curated set of extensions (a customized pgvector, pgvectorscale) plus its own Rust extension, so one CREATE EXTENSION exposes an ai.* / theodb.* surface. You generate embeddings, run vector + hybrid search, and call an LLM directly in SQL — against the same transactional rows as your operational data, with no ETL to a separate vector store.

The AI surface, in SQL

Once the extension is enabled, AI is just SQL. The database ships no model and stores no keys — you point it at any OpenAI-compatible endpoint via session settings.

CREATE EXTENSION IF NOT EXISTS theodb CASCADE;   -- pulls vector + vectorscale

-- Embeddings
SELECT theodb.embed('running shoes for trail');   -- → vector

-- Generation / classification, per row
SELECT ai.summarize(description)      AS gist,
       ai.analyze_sentiment(review)   AS mood
FROM products;

The unified query is the point — vector search, a relational JOIN, and an AI call in one transaction:

SELECT p.id, p.description,
       ai.summarize(p.description) AS gist          -- AI leg
FROM products p
JOIN inventory i ON i.product_id = p.id             -- relational JOIN
WHERE i.in_stock AND p.category_id = 3              -- relational filter
ORDER BY p.embedding <=> '[0.1, 0.2, ...]'::vector   -- vector leg
LIMIT 5;

Capabilities

Where to go next