vespa
Weaviate
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| vespa | Weaviate | |
|---|---|---|
| 4 | 76 | |
| 5,336 | 9,524 | |
| 2.5% | 5.7% | |
| 10.0 | 10.0 | |
| 6 days ago | 1 day ago | |
| Java | 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.
vespa
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Top 10 Best Vector Databases & Libraries
Vespa(4.3k ⭐) → A fully featured search engine and vector database. It supports vector search (ANN), lexical search, and search in structured data, all in the same query. Integrated machine-learned model inference allows you to apply AI to make sense of your data in real time.
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Vector database built for scalable similarity search
If ES doesn't work for you, I recommend Vespa. https://github.com/vespa-engine/vespa
Others have made other suggestions, but Vespa has two unique features. First it is battle tested at a large scale, second it supports combining the keyword and vector scores in several ways. The latter is something that other hybrid systems don't do very well in my experience including ES/Solr.
- ZincSearch – lightweight alternative to Elasticsearch written in Go
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MeiliSearch: A Minimalist Full-Text Search Engine
After looking at various alternatives, I'm thinking of trying out https://vespa.ai/ [0]
[0] https://github.com/vespa-engine/vespa
Weaviate
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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
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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.
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Choosing vector database: a side-by-side comparison
This will be solved in Weaviate https://github.com/weaviate/weaviate/issues/2424
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Who's hiring developer advocates? (October 2023)
Link to GitHub -->
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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?
Typesense - Open Source alternative to Algolia + Pinecone and an Easier-to-Use alternative to ElasticSearch ⚡ 🔍 ✨ Fast, typo tolerant, in-memory fuzzy Search Engine for building delightful search experiences
Milvus - A cloud-native vector database, storage for next generation AI applications
qdrant - Qdrant - High-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
faiss - A library for efficient similarity search and clustering of dense vectors.
pgvector - Open-source vector similarity search for Postgres
Infinispan - Infinispan is an open source data grid platform and highly scalable NoSQL cloud data store.
milvus-lite - A lightweight version of Milvus wrapped with Python.
jina - ☁️ Build multimodal AI applications with cloud-native stack
milli - Search engine library for Meilisearch ⚡️
vald - Vald. A Highly Scalable Distributed Vector Search Engine