Developer Advocate at Timescale
By popular demand, pgai Vectorizer is now a Python library and CLI that works with any self-hosted or managed Postgres database. See how we built it.
By Avthar Sewrathan
April 30th, 2025
Running analytical queries on Parquet files? Searching unstructured documents embeddings with pgvector? Get Postgres performance & S3 scalability in one place.
By Vineeth Pothulapati
April 30th, 2025
Looking for an open-source, high-performance vector database for large-scale workloads? We compare Qdrant vs. Postgres + pgvector + pgvectorscale.
By Avthar Sewrathan
April 29th, 2025
The integration of pgai Vectorizer with SQLAlchemy and LiteLLM will enable you to manage vector embeddings easily and seamlessly within your workflows. See how.
By Meshach Cisero
February 17th, 2025
While remarkable, proprietary LLMs force devs to give up privacy and control. Read along to learn our picks on the best components for an open-source AI stack.
By Matvey Arye
December 16th, 2024
Today’s vector databases disconnect embeddings from their source data. We should treat embeddings more like database indexes—here’s how.
By Matvey Arye
October 29th, 2024
What if testing your data with a new OpenAI embedding model was as easy as running a SQL query?
By Avthar Sewrathan
October 29th, 2024
Pgai Vectorizer makes testing and experimenting with different RAG chunking and formatting approaches easy, helping you improve your AI system faster.
By Avthar Sewrathan
October 29th, 2024
Learn how to pick the right approach to handle multi-tenancy for your use case when building multi-tenant RAG applications with PostgreSQL.
By Avthar Sewrathan
October 11th, 2024
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