SERVICES / DATA
EVIDENCED BY THE ARCHIVE
High-throughput, low-dependency data systems with measurement context attached.
WHO THIS IS FOR — Engineering work where throughput and correctness must arrive with the measurement methodology attached, not just a headline number.
THE PROBLEM IT ADDRESSES
- Pipelines whose performance is claimed without a stated methodology or hardware context.
- Dependency-heavy stacks where a single library upgrade changes numeric results.
- Intermediate financial models entangled with presentation, so they cannot be reused or audited.
EXPECTED DELIVERABLES
- A pipeline with an explicit intermediate model, separated from presentation and storage.
- Published benchmark output: throughput, latency and memory with methodology attached.
- Reproducible builds and test suites run in CI on every change.
OUT OF SCOPE
- Cloud platform operations, deployment or on-call ownership after handover.
- Data licensing or procurement.
TECHNICAL APPROACH
HOW THE WORK IS DONE
High-throughput data pipelines: ingestion, transformation and query layers built for scale and exactness.
SCHEMATIC · DATA ENGINEERING
METHODS
487,421 rec/s pipeline · POSIX mmap · Zero-dependency C11 · NSDC Data Standards
EVIDENCE
billing-data-gateway's zero-dependency C11 pipeline sustains 487,421 rec/s over POSIX mmap, and "Exact Decimal Arithmetic in Market Data" covers the exactness side.
RELEVANT PROJECT EXAMPLES
WORK THAT PROVES IT
RELATED RESEARCH
THE WRITTEN RECORD
LIMITATIONS
SCOPE & LIMITS
- Benchmarks are measured on stated hardware with stated data; other environments will differ.
- Throughput figures describe the engine, not end-to-end system latency under production load.
WORKING PROCESS
HOW THIS ENGAGEMENT RUNS
- 01EXPLICIT INTERMEDIATE MODEL
- 02BENCHMARK WITH METHODOLOGY
- 03REPRODUCIBLE BUILDS
- 04TESTS IN CI ON EVERY CHANGE
Each stage produces something checkable. The full process, with what every stage produces across all work, lives on the process page. Every engagement starts the same way: describe the problem, the data, and the evidence that would count as success.