Milvus Performance Evaluation 2023
Milvus 2.2.3 is now 4X faster than Milvus 2.0
In this technical paper, we’ll compare the performance and features of Milvus for vector collections workloads, specifically looking at the query performance (latency and throughput) and scalability (billion scale collection and multiple replicas).
This data should prove valuable to developers and architects evaluating the suitability of these technologies for their use case. Specifically, similarity search use cases involve building semantic text search, targeted advertising, e-commerce product recommendation engines, user-generated content (UGC) recommenders, risk-control and anti-fraud systems, and new drug discovery.
Our goal with this benchmark test was to create a consistent, up-to-date comparison that reflects the latest developments in Milvus. Periodically, we’ll re-run these benchmarks and update this document with our findings. All of the code for these benchmarks is available on GitHub. Feel free to open up issues or pull requests on that repository if you have any questions, comments, or suggestions.
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