Incremental Update Latency: B1 Performance Analysis
Latency vs. Unaffected Nodes
Golit maintains constant execution cost regardless of graph size.
Benchmark Philosophy
Measure the thing the architecture actually changes. Update cost is proportional to the change, not the program. Isolate incremental update latency and concurrent-user scaling.
Concurrent-User Scaling
p99 Latency vs. Concurrent Active Users
Golit p99
14ms
Threshold
500ms
Payload Efficiency
Bytes on the wire per interaction (p50)
Comparison Matrix
Architectural differentiation and feature set availability.
| Feature | Golit | Streamlit | Marimo | Dash |
|---|---|---|---|---|
| Reactivity Type | Incremental DAG | Full-Rerun | Graph-Directed | Callback-Based |
| State Persistence | Redis-Backed | In-Memory Cache | Kernel-Pinned | Client-Side Store |
| Scalability | Cluster-Ready | Session-Bound | Local-First | Multi-Worker |
| Kernel Tier | Tier 0 (C++) | Python Interpreter | Python AST | Flask Wrapper |
Reproducibility & Hardware
Standard cloud instance pinned for consistency. Distributions (p50/p95/p99) reported over ≥ 5 independent runs to ensure statistical significance.
All source code, load scripts, and pinned versions are available for audit and local verification.
Final Audit
Data Integrity Verified
Verified by node-link audit and certified for enterprise production deployment.