sqlite-vss
Weaviate
sqlite-vss | Weaviate | |
---|---|---|
17 | 76 | |
1,455 | 9,587 | |
- | 3.7% | |
8.0 | 10.0 | |
about 2 months ago | 3 days ago | |
C++ | Go | |
MIT License | BSD 3-clause "New" or "Revised" License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
sqlite-vss
-
I'm writing a new vector search SQLite Extension
I guess this is an answer to the GitHub issue I opened against SQLite-vss a couple of months ago?
https://github.com/asg017/sqlite-vss/issues/124
-
Embeddings are a good starting point for the AI curious app developer
Perhaps sqlite-vss? It adds vector searches to sqlite.
https://github.com/asg017/sqlite-vss
-
How to Enhance Content with Semantify
Utilizing sqlite-vss to store and query vector embeddings managed by a local SQLite database, Semantify conducts fast, precise vector searches within these embeddings to find and recommend relevant content, ensuring readers are presented with articles that truly match their interests.
-
SQLite vs. Chroma: A Comparative Analysis for Managing Vector Embeddings
Whether you’re navigating through well-known options like SQLite, enriched with the sqlite-vss extension, or exploring other avenues like Chroma, an open-source vector database, selecting the right tool is paramount. This article compares these two choices, guiding you through the pros and cons of each, helping you choose the right tool for storing and querying vector embeddings for your project.
-
Vector database is not a separate database category
Here is a SQLite extension that uses Faiss under the hood.
https://github.com/asg017/sqlite-vss
Not associated with the project, just love SQLite and find it very useful.
- SQLite-Vss: A SQLite Extension for Vector Search
-
Introduction to Vector Search and Embeddings
Vector Databases: As your data grows, efficiently searching through millions of vectors can become a challenge. Specialized vector databases like FAISS, Annoy, or Elasticsearch's vector search capabilities can be explored to manage and search through large-scale vector data. Your sentence is grammatically correct. In addition, databases like SQLite and PostgreSQL have extensions, such as sqlite-vss and pgvector, that can be used to store and query vector embeddings, respectively.
-
The Problem with LangChain
I had a go at one of those a few months ago: https://datasette.io/plugins/datasette-faiss
Alex Garcia built a better one here as a SQLite Rust extension: https://github.com/asg017/sqlite-vss
-
Every request, every microsecond: scalable machine learning at Cloudflare
Since the problem domain is that of anomaly detection from constructed request feature embeddings, I wonder if an ANN-search methodology using an embedded database (such as https://github.com/asg017/sqlite-vss or similar) was explored.
-
Disrupting the AI Scene with Open Source and Open Innovation
As I searched for "sqlite vector plugin" I didn't find any results, before a couple of weeks ago. Two weeks ago I found Alex' SQLite VSS plugin for SQLite. The library was an amazing piece of engineering from an "idea perspective". However, as I started playing around with it, I realised it was ipso facto like "Titanic". Beautiful and amazing, but destined to leak water and sink to the bottom of the ocean because of what we software engineers refers to as "memory leaks".
Weaviate
-
pgvecto.rs alternatives - qdrant and Weaviate
3 projects | 13 Mar 2024
- FLaNK Stack 29 Jan 2024
- Qdrant, the Vector Search Database, raised $28M in a Series A round
-
How to use Weaviate to store and query vector embeddings
In this tutorial, I introduce Weaviate, an open-source vector database, with the thenlper/gte-base embedding model from Alibaba, through Hugging Face's transformers library.
-
Choosing vector database: a side-by-side comparison
This will be solved in Weaviate https://github.com/weaviate/weaviate/issues/2424
-
Who's hiring developer advocates? (October 2023)
Link to GitHub -->
-
Do we think about vector dbs wrong?
Hey @rvrs, I work on Weaviate and we are doing some improvements around increasing write throughput:
1. gRPC. Using gRPC to write vectors has had a really nice performance boost. It is released in Weaviate core but here is still some work on do on the clients. Feel free to get in contact if you would like to try it out.
2. Parameter tuning. lowering `efConstruction` can speed up imports.
3. We are also working on async indexing https://github.com/weaviate/weaviate/issues/3463 which will further speed things up.
In comparison with pgvector, Weaviate has more flexible query options such as hybrid search and quantization to save memory on larger datasets.
- Weaviate vector database
- Weaviate 1.21: Support for ImageBind and GPT4all and more
- Weaviate Vector Database
What are some alternatives?
semantic-kernel - Integrate cutting-edge LLM technology quickly and easily into your apps
Milvus - A cloud-native vector database, storage for next generation AI applications
chroma - the AI-native open-source embedding database
faiss - A library for efficient similarity search and clustering of dense vectors.
pgvector-go - pgvector support for Go
pgvector - Open-source vector similarity search for Postgres
milvus-lite - A lightweight version of Milvus wrapped with Python.
qdrant - Qdrant - High-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
typesense-instantsearch-semantic-search-demo - A demo that shows how to build a semantic search experience with Typesense's vector search feature and Instantsearch.js
jina - ☁️ Build multimodal AI applications with cloud-native stack
txtai - 💡 All-in-one open-source embeddings database for semantic search, LLM orchestration and language model workflows
vald - Vald. A Highly Scalable Distributed Vector Search Engine