knowhere
Weaviate
| knowhere | Weaviate | |
|---|---|---|
| 1 | 77 | |
| 181 | 9,713 | |
| - | 4.9% | |
| 3.5 | 10.0 | |
| 9 months ago | 5 days ago | |
| C++ | Go | |
| Apache License 2.0 | 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.
knowhere
-
Vector search just got up to 10x faster and vertically scalable
Just to clarify, Milvus is much more than a wrapper around FAISS. Our vector search component called Knowhere (https://github.com/milvus-io/knowhere) utilizes FAISS and Annoy and will soon include ScaNN, DiskANN, and in-house vector indexes as well. Milvus then uses Knowhere as the compute engine, and implements a variety of database functions such as horizontal scaling, caching, replication, failover, and object storage on top of Knowhere. If you're interested, I recommend checking out our architecture page (https://milvus.io/docs/architecture_overview.md).
Weaviate
- Weaviate – A cloud-native, open-source vector database
-
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
What are some alternatives?
nmslib - Non-Metric Space Library (NMSLIB): An efficient similarity search library and a toolkit for evaluation of k-NN methods for generic non-metric spaces.
Milvus - A cloud-native vector database, storage for next generation AI applications
pgvector - Open-source vector similarity search for Postgres
faiss - A library for efficient similarity search and clustering of dense vectors.
qdrant - Qdrant - High-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
jina - ☁️ Build multimodal AI applications with cloud-native stack
vald - Vald. A Highly Scalable Distributed Vector Search Engine
ChatterBot - ChatterBot is a machine learning, conversational dialog engine for creating chat bots
marqo - Unified embedding generation and search engine. Also available on cloud - cloud.marqo.ai
go - The Go programming language
annoy - Approximate Nearest Neighbors in C++/Python optimized for memory usage and loading/saving to disk