Sachin Frayne
Senior Support Engineer
Jingra: A Reproducible Framework for Vector Search Benchmarking
Jingra is an open source benchmarking framework that runs the same vector search workload across Elasticsearch, OpenSearch and Qdrant so you can compare engines under identical, reproducible conditions.
The hash() Elasticsearch won't name and the 12 bytes that prove it's Murmur3
Elasticsearch's routing formula uses MurmurHash3, but the docs never say so. This post names the function, walks through the full shard calculation, and shows you how to reproduce it externally.
Elasticsearch DiskBBQ delivers 7x faster vector search than Qdrant on network-attached storage
Elasticsearch DiskBBQ achieves up to 7x higher vector search throughput than Qdrant at comparable recall on network-attached storage. Explore the benchmark methodology and full results.
How to implement Better Binary Quantization (BBQ) into your use case
Explore why you would implement Better Binary Quantization (BBQ) in your use case and how to do it.
Elasticsearch vector search is up to 8x faster than OpenSearch
Exploring filtered vector search benchmarks of OpenSearch vs. Elasticsearch and why vector search performance is critical for context-engineered systems.
