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We recently benchmarked AnuDB, a lightweight embedded database built on top of RocksDB, against SQLite on a Raspberry Pi. The performance difference, especially for parallel operations, was dramatic.GitHub Links:AnuDBBenchmark: https://github.com/hash-anu/AnuDBBenchmarkAnuDB (Core): https://github.com/hash-anu/AnuDBWhy Compare AnuDB and SQLite?
SQLite is excellent for many embedded use cases — it’s simple, battle-tested, and extremely reliable. But it doesn't scale well when parallelism or concurrent writes are required.AnuDB, built over RocksDB, offers better concurrency out of the box. We wanted to measure the practical differences using real benchmarks on a Raspberry Pi.Benchmark Setup
Platform: Raspberry Pi 2 (ARMv7)Benchmarked operations: Insert, Query, Update, Delete, ParallelAnuDB uses RocksDB and MsgPack serializationSQLite uses raw data, with WAL mode enabled for fairnessKey Results
Insert:AnuDB: 448 ops/secSQLite: 838 ops/secQuery:AnuDB: 54 ops/secSQLite: 30 ops/secUpdate:AnuDB: 408 ops/secSQLite: 600 ops/secDelete:AnuDB: 555 ops/secSQLite: 1942 ops/secParallel (10 threads):AnuDB: 412 ops/secSQLite: 1.4 ops/sec (!)In the parallel case, AnuDB was over 279x faster than SQLite.Why the Huge Parallel Difference?
SQLite, even with WAL mode, uses global database-level locks. It’s not designed for high-concurrency scenarios.RocksDB (used in AnuDB) supports:Fine-grained lockingConcurrent readers/writersBetter parallelism using LSM-tree architectureThis explains why AnuDB significantly outperforms SQLite under threaded workloads.Try It Yourself
Clone the repo:git clone https://github.com/hash-anu/AnuDBBenchmark
cd AnuDBBenchmark
./build.sh /path/to/AnuDB /path/to/sqlite
./benchmarkResults are saved to benchmark_results.csv.When to Use AnuDB
Use AnuDB if:You need embedded storage with high concurrencyYou’re dealing with telemetry, sensor data, or parallel workloadsYou want something lightweight and faster than SQLite under loadStick with SQLite if:You need SQL compatibilityYou value mature ecosystem/toolingFeedback Welcome
This is an early experiment. We’re actively developing AnuDB and would love feedback:Is our benchmark fair?Where could we optimize further?Would this be useful in your embedded project?
Comments URL: https://news.ycombinator.com/item?id=43903414
Points: 5
# Comments: 0
SQLite is excellent for many embedded use cases — it’s simple, battle-tested, and extremely reliable. But it doesn't scale well when parallelism or concurrent writes are required.AnuDB, built over RocksDB, offers better concurrency out of the box. We wanted to measure the practical differences using real benchmarks on a Raspberry Pi.Benchmark Setup
Platform: Raspberry Pi 2 (ARMv7)Benchmarked operations: Insert, Query, Update, Delete, ParallelAnuDB uses RocksDB and MsgPack serializationSQLite uses raw data, with WAL mode enabled for fairnessKey Results
Insert:AnuDB: 448 ops/secSQLite: 838 ops/secQuery:AnuDB: 54 ops/secSQLite: 30 ops/secUpdate:AnuDB: 408 ops/secSQLite: 600 ops/secDelete:AnuDB: 555 ops/secSQLite: 1942 ops/secParallel (10 threads):AnuDB: 412 ops/secSQLite: 1.4 ops/sec (!)In the parallel case, AnuDB was over 279x faster than SQLite.Why the Huge Parallel Difference?
SQLite, even with WAL mode, uses global database-level locks. It’s not designed for high-concurrency scenarios.RocksDB (used in AnuDB) supports:Fine-grained lockingConcurrent readers/writersBetter parallelism using LSM-tree architectureThis explains why AnuDB significantly outperforms SQLite under threaded workloads.Try It Yourself
Clone the repo:git clone https://github.com/hash-anu/AnuDBBenchmark
cd AnuDBBenchmark
./build.sh /path/to/AnuDB /path/to/sqlite
./benchmarkResults are saved to benchmark_results.csv.When to Use AnuDB
Use AnuDB if:You need embedded storage with high concurrencyYou’re dealing with telemetry, sensor data, or parallel workloadsYou want something lightweight and faster than SQLite under loadStick with SQLite if:You need SQL compatibilityYou value mature ecosystem/toolingFeedback Welcome
This is an early experiment. We’re actively developing AnuDB and would love feedback:Is our benchmark fair?Where could we optimize further?Would this be useful in your embedded project?
Comments URL: https://news.ycombinator.com/item?id=43903414
Points: 5
# Comments: 0
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