Run inference on ONNX models inside your Postgres database (and a Tensor type)
pgext.cloud · Source code · Documentation · Control file
| Package | pgtensor |
|---|---|
| Version | 0.0.0 |
| Repository | Unspecified |
| Extension type | Standard |
| Project status | Active |
| Requires CREATE EXTENSION | Yes |
| Requires preload | No |
| Trusted | No |
| Relocatable | No |
| Stars | 1 |
| Latest commit | 2026-01-06 |
| Catalogue updated | 2026-08-30 |
| pg_onnx | ONNX Runtime integrated with PostgreSQL. Perform ML inference with data in your database. |
| pgpyml | Run scikit-learn machine-learning models inside PostgreSQL through PL/Python functions and triggers. |
| pgdl | PostgreSQL extension for deep learning model inference and vector storage inside the database. |
| aqua | In-database neural user-defined functions for machine-learning inference. |
| pg_gembed | Generate embeddings inside PostgreSQL |
| pg_deeplake | Deeplake is AI Data Runtime for Agents. It provides serverless postgres with a multimodal datalake, enabling scalable retrieval and training. |
| pg4ml | Machine learning framework for PostgreSQL |
| kmeans | K-means clustering window function for PostgreSQL |