What does HackerNews think of pg_embedding?

Hierarchical Navigable Small World (HNSW) algorithm for vector similarity search in PostgreSQL

Language: C

Pgvector 0.5.0 Feature Highlights and how tos | Aug 2023
Congratulations, can anyone give an insight on how this compares to pg_embedding [0] (Postgres and use HNSW). Or the use-cases compared to other victor databases. It’s getting hard to keep up what’s happening in the LLM scene.

[0] https://github.com/neondatabase/pg_embedding

An early look at HNSW performance with pgvector | Aug 2023
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A couple: https://github.com/neondatabase/pg_embedding
How to add an AI Code Copilot to your product using GPT4 | Aug 2023
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I think windmill can go a step further if you add the vectordb to the same database https://github.com/neondatabase/pg_embedding
https://news.ycombinator.com/item?id=36988075 | Aug 2023
A few weeks back, we released pg_embedding[1], a new extension for Postgres and LangChain which introduced Hierarchical Navigable Small Worlds (HNSW) indexes for vector similarity search. This new indexing method resulted in 20x faster queries at a 99% accuracy compared to traditional IVFFlat indexing[2].

Today, we released a new version which includes the following improvements:

1. The HNSW index is now constructed on disk instead of in memory

2. The extension now supports Cosine, Manhattan, and Euclidean distances

[1]: https://github.com/neondatabase/pg_embedding

[2]: https://neon.tech/blog/pg-embedding-extension-for-vector-sea...

20x faster than pgvector: HNSW index in Postgres with pg_embedding | Jul 2023
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https://github.com/neondatabase/pg_embedding
20x faster than pgvector: HNSW index in Postgres with pg_embedding | Jul 2023
I believe it's available here: https://github.com/neondatabase/pg_embedding/

It doesn't yet have a LICENSE file, so it's not strictly OS quite yet, but that might have been an oversight.