I’ve been working on AnuDB, a lightweight embedded key-value database backed by RocksDB, optimized for low-power devices like the Raspberry Pi.
It's designed as an alternative to SQLite in scenarios where high concurrency and write-heavy workloads matter.
I benchmarked AnuDB vs SQLite (with WAL mode) on a Raspberry Pi (ARMv7). Both were cross-compiled. Here are the results:
Benchmark: Operations per second (Ops/s)
Insert: AnuDB 448 | SQLite 839
Query: AnuDB 55 | SQLite 30
Update: AnuDB 408 | SQLite 600
Delete: AnuDB 556 | SQLite 1942
Parallel (10 threads): AnuDB 413 | SQLite 1.5
While SQLite is highly optimized for single-threaded operations, it struggles under multi-threaded writes. AnuDB, using RocksDB, handles parallel operations much better.
GitHub:
AnuDB: https://github.com/hash-anu/AnuDB
Benchmark: https://github.com/hash-anu/AnuDBBenchmark
Would love feedback on:
Use case suggestions
Benchmarking approaches
Whether this could be useful in your projects
Thanks!