Pgvecto.rs Alternatives

pgvecto.rs reviews and mentions

• PGVector's Missing Features
  3 projects | dev.to | 13 Sep 2024

  Pgvector is very slow, seconds to 10's of seconds, on filter and order by queries. Its maintainers are working on this as you can see in this currently 83 comment long issue on Github and pgvector.rs has made improvements as you can see here, but it's messy. I strongly believe that you don't want to be fighting through these issues when adding semantic search to your product. It's going to be a long term, hard fought struggle to keep up with pgvector's updates here and continuously tune it.

• Mongo but on Postgres and with strong consistency benefits
  9 projects | news.ycombinator.com | 7 Jul 2024
• My binary vector search is better than your FP32 vectors
  1 project | dev.to | 25 Mar 2024

  To evaluate the performance metrics in comparison to the original vector approach, we conducted benchmarking using the dbpedia-entities-openai3-text-embedding-3-large-3072-1M dataset. The benchmark was performed on a Google Cloud virtual machine (VM) with specifications of n2-standard-8, which includes 8 virtual CPUs and 32GB of memory. We used pgvecto.rs v0.2.1 as the vector database.

• pgvecto.rs 0.2: Unifying Relational Queries and Vector Search in PostgreSQL
  2 projects | dev.to | 13 Mar 2024

  Please check out our documentation for more details. We encourage you to try out pgvecto.rs, benchmark it against your workloads, and contribute your indexing innovations. Join our Discord community to connect with the developers and other users working to improve pgvecto.rs!

• pgvecto.rs alternatives - qdrant and Weaviate
  3 projects | 13 Mar 2024
• Milvus VS pgvecto.rs - a user suggested alternative
  2 projects | 13 Mar 2024
• You Shouldn't Invest in Vector Databases?
  4 projects | news.ycombinator.com | 25 Nov 2023

  It's kind of a tradeoff. Performance is just one factor when choosing the vector database. In pgvecto.rs https://github.com/tensorchord/pgvecto.rs, we store the index separately from PostgreSQL's internal storage, unlike pgvector's approach. This enable us to get multi-threaded indexing, async indexing without blocking the insertion, and faster search speed comparing to pgvector.

  I don't see any fundamental reason why the index in Postgres would be slower than a specialized vector database. The query pattern of the vector database is simply a point query using an index, similar to other queries in an OLTP system.

  The only limitation I see is scalability. It's not easy to make PostgreSQL distributed, but solutions like Citus exist, making it still possible.

  (I'm the author of pgvecto.rs)

• How We Made PostgreSQL a Better Vector Database
  2 projects | news.ycombinator.com | 25 Sep 2023

  Hi, we've solved the problem you mentioned! Please take a look on our open source postgres vector extension https://github.com/tensorchord/pgvecto.rs.

  Our index building process is significantly faster than pgvector on hnsw because we can utilize all the cores, whereas pgvector can only use one core. And for the filter support, we do support pre-filtering, which will guarantee enough results no matter the condition is.

• First Postgres Vector Extension with Filtering Support
  1 project | news.ycombinator.com | 28 Aug 2023

  Hi,

  In our previous post titled “Do we really need a specialized vector database?” on HN (https://news.ycombinator.com/item?id=37097004) we discussed the importance of using a Postgres-based solution for vector search. However, we acknowledged that existing Postgres vector extensions lack support for metadata filtering.

  We are excited to announce that we have now addressed this limitation. We are proud to be the first (https://github.com/tensorchord/pgvecto.rs) to enable conditional filtering directly on HNSW indexes within Postgres. This breakthrough allows for efficient and effective metadata filtering in combination with vector search, eliminating the tradeoff previously associated with using Postgres for this purpose.

  We invite you to explore our updated offering and experience the benefits of seamless metadata filtering within a Postgres-based vector search system.

• A Summary of LLMOps
  2 projects | news.ycombinator.com | 10 Aug 2023

  Yeah, I think in many cases you just need a vector search lib, instead of a DB.

  And in some other cases, you may want postgres vector extension e.g. https://github.com/tensorchord/pgvecto.rs instead of a specialized vector db.

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  www.saashub.com | 6 Oct 2024

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