Last year I shared many posts documenting MariaDB performance for vector search using ann-benchmarks. Performance was great in MariaDB 11 and this blog post explains that it is even better in MariaDB 12. This work was done by Small Datum LLC and sponsored by the MariaDB Foundation. My previous posts were published in January and February 2025.
tl;dr
Benchmark
This time I used the dbpedia-openai-X-angular tests for X in 100k, 500k and 1000k.
For hardware I used a larger server (Hetzner ax162-s) with 48 cores, 128G of RAM, Ubuntu 22.04 and HW RAID 10 using 2 NVMe devices.
For databases I used:
I had ps and vmstat running during the benchmark and confirmed there weren't storage reads as the table and index were cached by MariaDB and Postgres.
The command lines to run the benchmark using my helper scripts are:
bash rall.batch.sh v1 dbpedia-openai-100k-angular c32r128
bash rall.batch.sh v1 dbpedia-openai-500k-angular c32r128
bash rall.batch.sh v1 dbpedia-openai-1000k-angular c32r128
Results: dbpedia-openai-100k-angular
Summary
Results: dbpedia-openai-500k-angular
Summary
Results: dbpedia-openai-1000k-angular
Summary