Performance baselines

These are the steady-state numbers for the current release (2026.05.05.12), measured against the IBM Informix Developer Edition Docker container on loopback.

Codec micro-benchmarks

Operation	Mean	Throughput
`decode(int)` per cell	139 ns	7.2M ops/sec
`decode(varchar)` per cell	280 ns	3.6M ops/sec
`decode(decimal)` per cell	410 ns	2.4M ops/sec
`parse_tuple_payload` per row (5 cols)	1.4 µs	715K rows/sec

End-to-end

Operation	Mean	Throughput
`SELECT 1` round-trip	~140 µs	~7K queries/sec
1000-row SELECT	~1.0 ms	~990K rows/sec sustained
`executemany(1000)` in transaction	32 ms	~31,000 rows/sec
Pool acquire + query + release	295 µs	~3.4K queries/sec
Cold connect (login handshake)	11 ms	~90 connections/sec

vs IfxPy 3.0.5

Benchmark	IfxPy	informix-driver	Result
Single-row SELECT round-trip	118 µs	114 µs	comparable
~10-row server-side query	130 µs	159 µs	IfxPy 22% faster
Cold connect	11.0 ms	10.5 ms	comparable
`executemany(1k)`	23.5 ms	23.2 ms	tied
`executemany(10k)`	259 ms	161 ms	informix-driver 1.6× faster
`executemany(100k)`	2376 ms	1487 ms	informix-driver 1.6× faster
`SELECT 1k`	1.34 ms	1.72 ms	IfxPy 1.28×
`SELECT 10k`	11.7 ms	16.1 ms	IfxPy 1.07×
`SELECT 100k`	116 ms	169 ms	IfxPy 1.15×

For the methodology, IQR caveats, and reproduction instructions, see Compared to IfxPy.

Phase progression on bulk SELECT

Phase	100k-row SELECT	Ratio vs IfxPy
Phase 36	280 ms	2.40× slower
Phase 37 (per-column readers)	250 ms	2.10× slower
Phase 38 (codegen-inlined decoders)	237 ms	2.04× slower
Phase 39 (connection-scoped buffered reader)	169 ms	1.15× slower

The Phase 39 jump is documented in The buffered reader.

Reproducing

git clone https://git.supported.systems/warehack.ing/informix-db
cd informix-db
make ifx-up        # starts the dev container
make bench         # runs all benchmarks
make compare       # head-to-head vs IfxPy (handles IfxPy's install gauntlet)

For just the bulk-fetch progression:

pytest -m benchmark tests/benchmarks/test_select_scaling.py