Building Earth Index as a searchable planet has always been ambitious & we've made sure to use the right tools to make this a reality. We're happy to use @TensorChord's PostgreSQL extension to enable environmental action at this scale.
Read more here➡️blog.vectorchord.ai/3-billion-vect…
🎉 10M Docker Pulls for pgvecto.rs! 🚀
We’re thrilled to celebrate this incredible milestone for pgvecto.rs!
But the journey doesn’t stop here! Meet github.com/tensorchord/ve…, its successor, offering affordable disk-based PG vector search!
#PostgreSQL
HNSW is popular but has major drawbacks, like high memory use and complex updates. Disk-based solutions like IVF, especially with RabitQ, offer better scalability and efficiency. It's time to consider simpler alternatives! #VectorDatabases#HNSW#IVFblog.pgvecto.rs/why-hnsw-is-no…
> First, we’re introducing explicit functions that treat external object storage locations as first-class data citizens. Second, we’re integrating the ability to run LLMs directly within the Postgres platform.
Interview with my senior coworker, Torsten.
odbms.org/2024/10/on-edb…
We are thrilled to announce the release of our Terraform provider for PGVecto.rs Cloud. This new provider is designed to simplify the process of managing resources on our cloud service
blog.pgvecto.rs/introducing-te…
We're excited to announce the release of pg_bestmatch.rs, a PostgreSQL extension that brings the power of Best Matching 25 Score (BM25) text queries to your database, enhancing your ability to perform efficient and accurate text retrieval. blog.pgvecto.rs/pgbestmatchrs-…
There’s thousands of RAG techniques and tutorials, but which ones perform the best?
ARAGOG by Matous Eibich is one of the most comprehensive evaluation surveys on advanced RAG techniques, testing everything from “classic vector database” to reranking (@cohere, LLM) to MMR to…
TIL about binary vector search... apparently there's a trick where you can take an embedding vector like [0.0051, 0.017, -0.0186, -0.0185...] and turn that into a binary vector just reflecting if each value is > 0 - so [1, 1, -1, -1, ...] and still get useful cosine similarities!
It is important to note that this is closely tied to the embedding model being used. The benchmark we conducted specifically focused on OpenAI's text-embedding-3-large model.
Maybe some binary embedding models have better performance. e.g. @cohere@JinaAI_
It is important to note that this is closely tied to the embedding model being used. The benchmark we conducted specifically focused on OpenAI's text-embedding-3-large model.
Maybe some binary embedding models have better performance. e.g. @cohere@JinaAI_
After conducting a thorough benchmarking process using @qdrant_engine's dataset, we have discovered fascinating insights regarding the superiority of binary vectors and shortened vectors.
blog.pgvecto.rs/my-binary-vect…
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7K Followers 786 FollowingCo-founder and CEO @TensorChord, building postgres-based vector extension https://t.co/7WGvl1sR56 | Father of 1 cat | Married
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