benchmark
Collection of Qdrant benchmarks (by qdrant)
qdrant-client
Python client for Qdrant vector search engine (by qdrant)
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| benchmark | qdrant-client | |
|---|---|---|
| 1 | 2 | |
| 7 | 616 | |
| - | 13.1% | |
| 0.0 | 9.2 | |
| over 1 year ago | 3 days ago | |
| Python | Python | |
| - | Apache License 2.0 |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.
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.
benchmark
Posts with mentions or reviews of benchmark.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-01-18.
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[N] We just got funded for an open-source project to make Metric Learning practical.
Regarding Milvus. Well, there are a few essential differences between our projects: - Unlike Milvus, we perform filtering during the search in the vector index, which keeps retrieval complexity close to logarithmic - same as in original HNSW. - We can support complex types of filterable payloads like geo-points - it is not a trivial problem to keep the HNSW search graph connected during filtering. We solved it in our custom implementation of the HNSW index. - Unlike Milvus, we perform a query-planning phase to determine an optimal strategy of executing queries with filters - Qdrant uses Rust programming language - it gives us an advantage in avoiding stop-the-world issues of languages with garbage collection. We also have a retrieval speed benchmark - https://github.com/qdrant/benchmark.
qdrant-client
Posts with mentions or reviews of qdrant-client.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2024-04-05.
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Show HN: Chromem-go – Embeddable vector database for Go
Qdrant lib project https://github.com/tyrchen/qdrant-lib, Qdrant SDK has also support for local mode, which means embeddable https://github.com/qdrant/qdrant-client
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Vector Databases: A Technical Primer [pdf]
The qdrant clients support a local mode where you point to a file[0].
[0] -- https://github.com/qdrant/qdrant-client#local-mode
What are some alternatives?
When comparing benchmark and qdrant-client you can also consider the following projects:
fashion-mnist - A MNIST-like fashion product database. Benchmark :point_down:
usearch - Fast Open-Source Search & Clustering engine × for Vectors & 🔜 Strings × in C++, C, Python, JavaScript, Rust, Java, Objective-C, Swift, C#, GoLang, and Wolfram 🔍
towhee - Towhee is a framework that is dedicated to making neural data processing pipelines simple and fast.