Atlas Vector Search Performance Guide & Benchmarks

[Henry_Weller]

Hello all!

We’ve just released a comprehensive benchmark and performance guide for Atlas Vector Search to help you build and scale vector search systems with confidence.

This resource is designed to streamline your first large-scale vector search implementation (10M+ vectors) by providing:

• Ready-to-use configurations for key parameters:
  • Index sizing
  • Embedding model dimensions
  • Quantization strategies
  • numCandidates optimization
  • Filtering approaches
  • Search Node setup
  • Concurrency settings
• Performance analysis showing how to balance recall, latency, and cost as you adjust these parameters
• Tailored reading paths based on your primary optimization goal (whether that’s maximizing recall, minimizing latency, or reducing costs)

Resources:

• View the benchmark guide
• Explore our test framework on GitHub