All 159 Dependencies
Every package PostgresML depends on, ranked by repo health score.
PostgresML is a PostgreSQL extension that brings machine learning and large language model inference directly into the database engine. Built in Rust using the pgrx framework, it exposes SQL functions like pgml.train, pgml.predict, pgml.embed, pgml.rank, and pgml.transform that execute ML operations in the same process as PostgreSQL — eliminating external API calls, data serialization overhead, and the latency of moving data to separate model servers.
The core insight is architectural: data for ML systems is inherently larger and more dynamic than the models themselves, so it is more efficient to bring models to the data rather than constantly moving data to the models. PostgresML realizes this by embedding Python bindings (via PyO3) inside the Rust extension, enabling direct invocation of Hugging Face Transformers, scikit-learn, XGBoost, LightGBM, and other libraries from within SQL queries — with optional GPU acceleration through CUDA.
The ecosystem extends beyond the extension itself. The project includes a Rocket-based web dashboard for managing models and visualizing metrics, a multi-language SDK (Rust, Python, JavaScript, C) for building RAG pipelines, integration with pgvector for approximate nearest neighbor search, and pgcat for horizontal connection pooling and sharding. Both self-hosted Docker deployments and a managed cloud service are available, making it accessible from local development to production-scale workloads.
