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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
Nice library with many features. But I do not always understand the focus on memory usage. I guess that the reason behind this is that less memory allocations, have a positive effect on execution times. In a parser, where you often have to compare identifiers, it is a good idea to put all strings for identifiers into a unique pointer with the help of a hash table.
In my interpreting parser [1] I use a hexa hash tree [2] for storing identifiers. It is not very memory efficient, but very fast. It turns every string (from the input buffer) into a unique pointer for that string pointing to a copy of the string. In this way comparing string (identifiers) is equivalent to comparing pointers.
The idea of the hexa hash tree is that is a tree where each node has sixteen child nodes. Which node is selected is based on a step wise evaluated hash function that first takes the lower four bytes of the string, and after reaching the end of the string, the higher four bytes of the string. The nodes often taken up more memory space than the strings themselves.
[1] https://github.com/FransFaase/IParse/
[2] https://github.com/FransFaase/IParse/blob/master/software/Id...