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pypyodbc speed
With the simple benchmark script on GitHub, below is the performance scores (seconds, lower is better) on Windows
The seconds used to operate 20,000 records on my Lenovo Dual-Core Celeron 2.1G , 3G RAM laptop :
Running with pypyodbc 1.3.4
Write time: 9.735416889190674 R & W time: 12.324021816253662 Read time: 0.9204015731811523
Running with pypyodbc 1.3.4
Write time: 8.36199998856 R & W time: 9.34499979019 Read time: 0.421000003815
Running with pypyodbc 1.3.0
Write time: 9.97799992561 R & W time: 11.7869999409 Read time: 0.910000085831
Running with pypyodbc 1.2.1
Write time: 9.7380001545 R & W time: 12.2130000591 Read time: 1.60899996758
pyodbc on CPython 2.7.6
Running with pyodbc 3.0.6
Write time: 12.9730000496 R & W time: 12.5540001392 Read time: 0.18799996376
Running with pypyodbc 1.3.2 odbcjt32.dll
Write time: 7.72200012207 R & W time: 9.39100003242 Read time: 0.483999967575
Running with pypyodbc 1.2.1
Write time: 9.57299995422 R & W time: 10.9049999714 Read time: 0.707999944687
Running with pypyodbc 1.2.1
Write time: 10.2185821533 R & W time: 15.8019104004 Read time: 2.62014770508
The seconds used to operate 20,000 records:
Running with pypyodbc 1.3.0 sqlncli10.dll
Write time: 13.2389998436 R & W time: 15.9130001068 Read time: 0.920000076294
Running with pypyodbc 1.2.1 sqlncli10.dll
Write time: 12.4639999866 R & W time: 15.6489999294 Read time: 1.54399991035
pyodbc on CPython 2.7.6
Running with pypyodbc 3.0.6 sqlncli10.dll
Write time: 10.4210000038 R & W time: 10.6079998016 Read time: 0.141000032425
Running with pypyodbc 1.3.0 sqlncli10.dll
Write time: 12.7769999504 R & W time: 15.1629998684 Read time: 0.470999956131
Running with pypyodbc 1.2.1 sqlncli10.dll
Write time: 12.1679999828 R & W time: 14.9449999332 Read time: 0.763999938965