Verifiable Systems Benchmarks across 10,000 Notes
Sphene is engineered for deterministic, sub-millisecond local-first agent workflows under 50MB RAM (<25MB local-only). Below are empirical benchmarks measured on standard Linux x86_64 hardware comparing native systems engineering against heavy client runtimes.
Summary Benchmark: Sphene delivers <0.20ms SQLite FTS5 search queries, <1.5ms direct Stdio MCP tool invocations, and zero lock contention under concurrent agent writes, while maintaining an active footprint of under 50MB RAM (<25MB local-only).
| Performance Metric | Heavy Desktop / Shell-Wrapper Paradigm | Sphene v2.2 Native Systems Engine |
|---|---|---|
| Daemon RAM at Rest | 400 MB – 1.2 GB (Electron / Chromium web view) | < 25 MB RAM (Local daemon; <50MB with WireGuard relay) |
| Peak Indexing RAM (10k notes) | 1.4 GB – 2.6 GB (High GC churn & DOM tree) | < 25 MB RAM (Bounded batch indexing) |
| Full-Text Search Latency | 45 ms – 180 ms (Unindexed file / regex scan) | < 0.20 ms (Embedded SQLite FTS5 WAL) |
| Intra-Document AST Extraction | Full document loaded into context | < 0.05 ms (Pinpoint heading subtree) |
| Agent Tool Invocation Roundtrip | 120 ms – 380 ms (Bash subshell / pipe / curl) | < 1.5 ms (Direct Stdio JSON-RPC MCP) |
| Concurrency Failure Rate | Frequent file lock & race exceptions | 0.0% (Zero-Lock WAL) (5s busy queue + pool) |
| Agent Token Window Waste | 100% whole-file dump per update | Up to 95% reduction (AST-level section patch) |
| Cold-Boot Startup Time | 2,500 ms – 6,000 ms (Framework initialization) | < 15 ms (Instant native Go binary) |
Testing Methodology & Hardware Baseline
All benchmarks are executed on commodity hardware without synthetic advantages:
Hardware Platform
Intel Core i7-11800H @ 2.30GHz, 32GB RAM, standard NVMe SSD storage, running Ubuntu 24.04 LTS.
Dataset Characteristics
10,000 markdown notes containing YAML frontmatter, markdown headings, code blocks, task lists, and bidirectional wikilinks (~142MB raw text).
Reproducibility Commands
Verified using sphene index, sphene search, and standard Go benchmarking suites (go test -bench=.).
Experience Sub-Millisecond Knowledge Retrieval
Deploy Sphene locally in 60 seconds with native MCP tools enabled.
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