{"id":2717,"date":"2012-06-21T22:11:45","date_gmt":"2012-06-21T21:11:45","guid":{"rendered":"http:\/\/www.gamlor.info\/wordpress\/?p=2717"},"modified":"2021-07-03T13:31:49","modified_gmt":"2021-07-03T12:31:49","slug":"some-performance-numbers-with-akka-async-sql","status":"publish","type":"post","link":"https:\/\/www.gamlor.info\/wordpress\/2012\/06\/some-performance-numbers-with-akka-async-sql\/","title":{"rendered":"Some Performance Numbers With Akka Async SQL"},"content":{"rendered":"

A while back I wrote about my small Async SQL library for Akka and its asynchronous MySQL driver<\/a>. Besides a few tiny fixes I’ve added nothing new recently.
\nHowever I want to share a few number from my performance experiments.<\/p>\n

\"Racing<\/a>

Racing Stuff<\/p><\/div>\n

Good Benchmarking, Science for itself<\/h2>\n

Good benchmarking is a small science for itself. Creating a balanced benchmark, ensure equal conditions for multiple runs, cranking out usable numbers, do proper analysis etc. I didn’t do that. I just wrote some code, ran that stuff and compared the numbers.
\nIn the end it heavily depends on your scenario anyway. For example when you run trivial queries against a local database, then JDBC will probably win, since it only blocks a thread very briefly. If you add web-like latencies to the database communication, then my ADBCJ solution has an huge advantage.<\/p>\n

The Benchmark Scenario<\/h2>\n

This is basically the benchmark scenario which I measured. It simulates a web like application.<\/p>\n