postgresml/postgresml

Health v2 · maintenance only

Adoption not part of the score

6821 stars · 363 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

PostgresML is a PostgreSQL extension that brings machine learning and AI inference directly into the database, with GPU acceleration and pgvector-based vector search. It lets you run LLMs, embeddings, RAG pipelines, and supervised learning via SQL without moving data to separate ML services.

Use cases

• build a RAG chatbot without a separate vector database
• generate embeddings for text stored in Postgres using SQL
• run LLM inference and text generation inside the database
• train and deploy classification and regression models on data in Postgres
• improve search results with semantic vector search and ranking
• fine-tune Hugging Face models on your own data
• consolidate vector DB, embedding service, and LLM API into one database

When to choose

• your data already lives in Postgres and you want ML/AI close to it
• you want to simplify an AI stack by replacing separate vector DB, embedding, and inference services
• you need GPU-accelerated inference with lower latency than HTTP-based model serving
• you prefer SQL as the interface for ML workflows
• data privacy requires keeping models and data together

When to avoid

• you need a lightweight standalone vector store without a full Postgres deployment
• your ML workloads are better served by specialized frameworks like PyTorch or dedicated serving stacks
• you cannot run GPU-backed Postgres infrastructure and lack cloud budget
• you need non-Postgres databases or multi-database ML orchestration

Facets

library · maturity active

vector-database machine-learning llm-inference rag search-engine nlp machine-learning large-language-models databases artificial-intelligence self-hosted cloud python rust postgres-extension pgvector huggingface gpu-acceleration in-database-ml sql embeddings vector-search fine-tuning retrieval-augmented-generation search natural-language-processing linux docker gpu

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markdown · JSON · MCP: product_card(name="postgresml/postgresml")