Practical overview
When it fits
Use it when you need workload-based throughput and cost-performance comparisons for fully managed vector database services.
Who it is for
- Teams comparing fully managed vector database services
- Developers measuring vector-search or filtered-search throughput
- People evaluating monthly cost per 100 QPS across services
Documented uses
- Measure queries per second for vector search.
- Measure queries per second for filtered vector search.
- Compare monthly cost per 100 QPS across services.
- Run documented benchmark workloads and visualize their results.
Requirements & limits
- The benchmark focuses on fully managed services.
- It reports QPS and monthly cost per 100 QPS as distinct comparison measures.
- Benchmark execution instructions and result-visualization guidance are provided separately.
Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.
Install the benchmark's client requirements
Prepare the benchmark client with the repository's required Python libraries.
Before you start
- A client machine for running the benchmark
- The benchmark repository and its requirements.txt file
Steps
Install the required libraries with the command below.
pip install -r requirements.txtContinue with the repository's step-by-step benchmark guide for the cloud service you want to test.
Expected outcome
The client has the listed libraries installed and is ready for the documented service-specific benchmark instructions.
Guide limitations
- This setup step alone does not run a benchmark or produce results.
Compare options for Vector search
These projects document a common task and share a project role. This is a source-based comparison, not an execution benchmark or a guarantee of interchangeability.
| Project | Documented purpose | Platform | Access and requirements |
|---|---|---|---|
| MyScale Vector Database Benchmark | Measure queries per second for vector search. | CLI | |
| Smallevals | Generate synthetic questions from chunks or documents for retrieval evaluation. | Linux, macOS, Self-hosted, Windows | Smallevals is presented as a public Python repository and documents installation with pip. The repository information supplied does not identify a license. |
Sources & review
Source record details
- Source availability
- Active
- Sources checked
- 17 October 2026
- Original website title
- myscale/vector-db-benchmark · Official homepage title · retained in its source language
Related options
Qdrant vector-db-benchmark — The repository identifies itself as a fork tailored to benchmarking fully managed vector databases.