This page provides guidance figures for detection speeds, memory usage and startup times for Pattern and Trie algorithms. Pattern is more memory efficient and can be run directly from disk while Trie requires considerably more main memory but delivers millions of detections per second. For more information check out the how device detection works page.

Results stated are detections per core on a quad core i7 2.2GHz CPU.

Below is a table of performance metrics relating to the Python Pattern API. It shows the detection speed for a single request for each data set and where applicable also the mode of operation used.

	Lite	Premium	Enterprise
Detections Per Second	55865	49751	43668
Time Per Detection (ms)	0.0179	0.0201	0.0229

	Lite	Premium	Enterprise
Startup Time (ms)	16.63	29.95	34.35
Average Memory Usage (Mb)	54	109	147

Below is a table of performance metrics relating to the Python Hash Trie API. It shows the detection speed for a single request for each data set and where applicable also the mode of operation used.

 

Single Thread	Lite	Enterprise
Detections Per Second	559,394	572,671
Time Per Detection (ms)	0.001788	0.001747

 

	Lite	Enterprise
Startup Time (ms)	63	79
Average Memory Usage (Mb)	116	142