Weaviate
Milvus
Our great sponsors
Weaviate | Milvus | |
---|---|---|
76 | 103 | |
9,181 | 26,298 | |
5.5% | 3.5% | |
10.0 | 10.0 | |
7 days ago | about 8 hours ago | |
Go | Go | |
BSD 3-clause "New" or "Revised" License | Apache License 2.0 |
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.
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.
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Pros and cons of vector search in elastic?
Highly opinionated as I'm working for Weaviate, so take my comment with a large portion of salt.
My highly opinionated view is that for Elastic, they're not really open source and the dependency on Java of the Lucene ecosystem is a big disadvantage, so as you already said, speed, they're getting better at this, but if you need to scale, this problem scales with you.
So if you already have ELK stack and don't need to scale, sure go for it otherwise, Weaviate offers real open source, so use it for free on your own infrastructure https://github.com/weaviate/weaviate
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Lost on LangChain: Can someone help with the Question Answer concept?
If you do not wish to store your private data on pinecone you can use open source alternatives like Weaviate where you can spin up your own instance. Other option could be to use Agents. You'll need to find sutaible agent for your database which will allow LLMs to directly query data from your private database.
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Questions about memory, tree-of-thought, planning
I tried cromadb but had terrible performance and could not pin down the cause (likely a problem on my end). Weaviate was easy to setup and had excellent performance, this is probably what I will use in the future. Next on my list is txtinstruct, to finetune a model with data that does not change and using a vector db for everything else seems promising.
Milvus
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Milvus VS pgvecto.rs - a user suggested alternative
2 projects | 13 Mar 2024
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How to choose the right type of database
Milvus: An open-source vector database designed for AI and ML applications. It excels in handling large-scale vector similarity searches, making it suitable for recommendation systems, image and video retrieval, and natural language processing tasks.
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Simplifying the Milvus Selection Process
Github Repository
Selecting the right version of open-source Milvus is important to the success of any project leveraging vector search technology. With Milvus offering different versions of its vector database tailored to varying requirements, understanding the significance of selecting the correct version is key for achieving desired outcomes.
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7 Vector Databases Every Developer Should Know!
Milvus is an open-source vector database designed to handle large-scale similarity search and vector indexing. It supports multiple index types and offers highly efficient search capabilities, making it suitable for a wide range of AI and ML applications, including image and video recognition, natural language processing, and recommendation systems.
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Ask HN: Who is hiring? (February 2024)
Zilliz is hiring! We're looking for REMOTE and/or HYBRID roles in SF
Zilliz is the company behind Milvus (https://github.com/milvus-io/milvus), the most widely adopted vector database. Vector databases are a crucial piece of any technology stack looking to take advantage of unstructured data. Most recently and notably, Retrieval Augmented Generation (RAG). For RAG, vector databases like Milvus are used as the tool to inject customized data. In other words, vector databases make things like customized chat bots, personalized product recommendations, and more possible.
We are hiring for Developer Advocates, Senior+ Level Engineers and Product people, and Talent Acquisition. Check out all the roles here: https://zilliz.com/careers
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Qdrant, the Vector Search Database, raised $28M in a Series A round
Good on them, I know the crustaceans are out here happy about this raise for a Rust based Vector DB!
(now I'm gonna plug what I work on)
If you're interested in a more scalable vector database written in Go, check out Milvus (https://github.com/milvus-io/milvus)
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Open Source Advent Fun Wraps Up!
But before we do, I do want to say that 🤩 all these lovely Open-Source projects would love a little 🎉💕 love by getting a GitHub star ⭐ for their efforts. Including Open Source Milvus 🥰
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First 15 Open Source Advent projects
1. Milvus by Zilliz | Github
What are some alternatives?
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/
Elasticsearch - Free and Open, Distributed, RESTful Search Engine
Face Recognition - The world's simplest facial recognition api for Python and the command line
jina - ☁️ Build multimodal AI applications with cloud-native stack
vald - Vald. A Highly Scalable Distributed Vector Search Engine
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.
annoy - Approximate Nearest Neighbors in C++/Python optimized for memory usage and loading/saving to disk