Weaviate
bbolt
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Weaviate | bbolt | |
---|---|---|
76 | 18 | |
9,436 | 7,583 | |
4.8% | 2.5% | |
10.0 | 9.1 | |
5 days ago | 6 days ago | |
Go | Go | |
BSD 3-clause "New" or "Revised" License | MIT 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.
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
bbolt
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How to extract key-value versioning from BBoltDB in ETCD as a Go Code
Based on this [GitHub document](https://github.com/etcd-io/bbolt) for BBoltDB, we can understand that Go Code be used to create a BBoltDB database on the system. The key-values added & operations done on them in that Go Code are stored in the BBoltDB database.
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Locker: Store secrets on your local file system.
A Locker is a store on your file system (built on top of the amazing bbolt).
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Looking for fast, space-efficient key-lookup
- bbolt for storage on disk. In order to get the smallest db file size possible make sure you insert the keys in order and set:
- is it possible to create a social media with all apis without database saving all the data into a yml or a json?
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BoltDB performance hit with large values?
I'm wanting to store some wasm modules (as []byte) in BoltDB. Right now the modules are <1MB, but eventually, they could be 10-50MB in size. Is this going to reduce the performance of BoltDB all around, if the size of a value is this large? If it makes a difference, I'm using the Storm toolkit for querying.
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Open Source Databases in Go
bbolt - An embedded key/value database for Go.
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Help to learn multithreading in Go
For learning goroutines and channels, I usually recommend writing a program that reads from files and writes the data in a dummy database with something like https://github.com/etcd-io/bbolt. It's relatively simple and you're more likely to run into common manifestations of concurrency issues running disk operations.
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[Noob] Question about Channels
If you would like to explore usage of channels, I highly recommend writing a program that reads from files and writes the data in a dummy database with something like https://github.com/etcd-io/bbolt.
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A tiny NoSQL database
No transactions, no consistency guarantees, no benchmarks, global locks in the storage implementation, a collection is copied in its entirety on every insertion to it...I realize it's not for the same use case as MySQL or MongoDB, but a more obvious comparison here is e.g. https://github.com/etcd-io/bbolt. So why should someone use this over bbolt?
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A pure Go embedded SQL database
use go-sqlite3 to work with sqlite3 is one choice.
https://github.com/etcd-io/bbolt is another pure go option.
cznic seems like an alternative to bbolt. nice to have some options.
What are some alternatives?
Milvus - A cloud-native vector database, storage for next generation AI applications
badger - Fast key-value DB in Go.
faiss - A library for efficient similarity search and clustering of dense vectors.
bolt
pgvector - Open-source vector similarity search for Postgres
goleveldb - LevelDB key/value database in Go.
qdrant - Qdrant - High-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
go-sqlite - Low-level Go interface to SQLite 3
jina - ☁️ Build multimodal AI applications with cloud-native stack
buntdb - BuntDB is an embeddable, in-memory key/value database for Go with custom indexing and geospatial support
vald - Vald. A Highly Scalable Distributed Vector Search Engine
BigCache - Efficient cache for gigabytes of data written in Go.