Bench
Workloads shaped like real apps — RAG chunks, prefix catalogs, restarts, crash-loop — with a clear integrity gate. Throughput numbers below are for the PugDB / F4KVS engine on developer hardware.
Snapshot 2026-08-22 · embed pins v0.2.5 / v0.3.6 · server v0.2.0
Meso · RAG chunk ingest
100,000 × 4096 B · flow rag_chunk_ingest_v1
One-shot batch + WAL sync (native engine)
Full keyset listing for RAG-style prefixes
Hot random gets after ingest
What we optimize for
- ✓ High-throughput bulk writes with WAL durability
- ✓ Fast prefix / catalog scans for chunked corpora
- ✓ Zero-surprise restarts — row counts verified after reopen
- ✓ Embed path (C/Go) aligned with the native engine train
Methodology: product-shaped keys (chunk:…), fixed seed, developer NVMe workstation.
Results vary by hardware. Run recorded 2026-07-24; pins have moved forward, integrity gate is unchanged.
Reliability reval · Aug 2026
After the LSM hot-path merge: crash-loop then a two-hour soak on the server harness. The server is the reliability harness — production embed is still FFI + LSM.
50 × 1,000 ops, SIGKILL, 0 loss. 2026-08-17.
1,661,444 cache ops, 10/10 anchors after restart, 0 health failures. 2026-08-18.
Server 20k microbench @f52790c: put 9,070 / get 29,412 / mixed 37,594 ops/s · 0 errors.
Server path (YCSB, 10k)
Partitioned server workloads on the recorded YCSB A/B/D 10k matrix — a comparable, small campaign, not the homepage story.
- vs PostgreSQL: 3.7–4.5x (avg 4.1×)
- vs ScyllaDB: 2–3.8× (avg 2.63×)
YCSB A/B/D, 10K records, 512B values, 4 workers, 30s per workload, partitioned storage (server path)
Larger matrix (432 cells) · median, not mean
A longer head-to-head (Aug 2026) spans many modes. The median is the honest headline; the mean is inflated by easy cells, and some QL cells lose.
- vs PostgreSQL: median 9.49× (range 0.8–143.82×, n=144)
- vs ScyllaDB: median 1.85× (range 0.11–2.9×, n=142)
432-cell multi-system matrix; 60s measurement. Headline the median — some QL cells lose.