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Preetam "recently" blogged about catena, a time-series metric store. There was another blog post about benchmarking boltdb by a Fog Creek engineer, also looking to write a time series database. This is something of a pattern in the Go community, which already boasts seriesly, InfluxDB, and prometheus; there are almost certainly others. Time series data has been de rigueur at least since the Etsy's

Preetam "recently" blogged about catena, a time-series metric store. There was another blog post about benchmarking boltdb by a Fog Creek engineer, also looking to write a time series database. This is something of a pattern in the Go community, which already boasts seriesly, InfluxDB, and prometheus; there are almost certainly others. Time series data has been de rigueur at least since the Etsy's

A few weeks ago, Alex Gaynor gave a talk at waza entitled "Why Python, Ruby, and Javascript are slow". A video now available, and it is a good watch if you use any of these languages. Even if you don't, or have just viewed the slides, it is still thought provoking. He rightly cites (unsurprising, given his pypy experience) the old rags of dynamic typing or monkey patching being slow as being the m

Python has lots of built-in serialization methods. It has had a standard module called pickle for a very long time, and exposes its built-in trusted data marshaling routines in the marshal module. Since the release of Python 2.6 in October, 2008 it has also had a standard, well-tested json library. Since json's simple conceptual mapping to hash tables, smaller overhead, faster parsing, and ease of