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GeorgeandAndrey Vasnetsov
faad182279
* new: add filtered search bench draft * new: update filtered search benchmark post * new: render article * refactoring: add newlines * new: add filtered search bench file structure, add chart * fix: fix plot preselect * fix: fix canvas id * debug: debug js * debug: add benchmark filter search script to header * fix: fix filter search plot selection * new: update benchmark data * refactoring: remove commented code * fix: fix bench data * new: fix labels order * new: sort dataset labels * new: add some text * fix: fix descriptions * debug: fix mapping not allowed yaml parsing error * new: update bench data * fix: fix dataset name * new: update bench data * fix: fix qdrant kw small vocab * text for the articles * upd text * fix: fix typos * new: replace bars with scatter plots * fix: fix method calls * debug: add initializer * fix: replace debug const with variable * new: remove data based split, remain only one plot * fix: remove geo data for milvus * new: remove range data for weaviate * new: remove int 2048 for milvus, as it crashes at the moment * upd graphs * link --------- Co-authored-by: Andrey Vasnetsov <andrey@vasnetsov.com>
31 lines
1.4 KiB
Markdown
31 lines
1.4 KiB
Markdown
---
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draft: false
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id: 2
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title: How vector search databases should be tested?
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weight: 1
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---
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# Benchmarking Vector Search Engines
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As an Open Source vector search engine, we are often compared to the competitors and asked about our performance vs the other tools.
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But the answer was never simple, as the world of vector databases lacked a unified open benchmark that would show the differences.
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So we created one, making some bold assumptions about how it should be done.
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Here we describe why we think that’s the best way.
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That is why we perform our benchmarks on exactly the same hardware, which you can rent from any cloud provider.
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It does not guarantee the best performance, making the whole process affordable and reproducible, so you can easily repeat it yourself.
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So in our benchmarks, we **focus on the relative numbers**, so it is possible to **compare** the performance of different engines given equal resources.
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The list will be updated:
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* Upload & Search speed on single node - [Benchmark](/benchmarks/single-node-speed-benchmark/)
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* Filtered search benchmark - [Benchmark](/benchmarks/#filtered-search-benchmark)
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* Memory consumption benchmark - TBD
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* Cluster mode benchmark - TBD
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Some of our experiment design decisions are described at [F.A.Q Section](/benchmarks/#benchmarks-faq).
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Suggest your variants of what you want to test in our [Discord channel](https://qdrant.to/discord)!
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