pgvecto.rs

Scalable, Low-latency and Hybrid-enabled Vector Search in Postgres. Revolutionize Vector Search, not Database. (by tensorchord)

Pgvecto.rs Alternatives

Similar projects and alternatives to pgvecto.rs

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a better pgvecto.rs alternative or higher similarity.

pgvecto.rs reviews and mentions

Posts with mentions or reviews of pgvecto.rs. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-03-13.
  • 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.

  • An early look at HNSW performance with pgvector
    2 projects | news.ycombinator.com | 10 Aug 2023
    Seems that pgvector has a viable competitor extension: https://github.com/tensorchord/pgvecto.rs
  • 20x Faster as the Beginning: Introducing pgvecto.rs extension written in Rust
    1 project | /r/rust | 8 Aug 2023
    We are thrilled to announce the release of https://github.com/tensorchord/pgvecto.rs, a powerful Postgres extension for vector similarity search written in Rust. Its HNSW algorithm is 20x faster than pgvector at 90% recall. But speed is just the start - pgvecto.rs is architected to add new algorithms easily. We've made it an extensible architecture for contributors to implement the new indexes quickly, and we look forward to the open-source community driving pgvecto.rs to new heights!
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    www.influxdata.com | 29 Apr 2024
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Stats

Basic pgvecto.rs repo stats
17
1,375
9.3
10 days ago

tensorchord/pgvecto.rs is an open source project licensed under Apache License 2.0 which is an OSI approved license.

pgvecto.rs is marked as "self-hosted". This means that it can be used as a standalone application on its own.

The primary programming language of pgvecto.rs is Rust.


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