GitHub - s1ck/MongoDB-Timemachine: Evaluation of MongoDB for a usecase concerning time series data up to 1B measuring points. Exact and range matches using JSON Queries and Map Reduce are used to query the data. MongoDB is evaluated in a sharded and non-sharded environment.

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config		config
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src/de/uni/leipzig/bis/mongodb		src/de/uni/leipzig/bis/mongodb
.gitignore		.gitignore
README		README

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This project is an evaluation of MongoDB for a usecase where time series
data (up to 30M measuring points) has to be stored and queried. 
Queries are simple range queries (from - to timestamp) and simple filters,
like "all data from station x" or "all days where x was greater then y".

This is my first trial with MongoDB and I hope it will fulfill our needs :)

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Evaluation of MongoDB for a usecase concerning time series data up to 1B measuring points. Exact and range matches using JSON Queries and Map Reduce are used to query the data. MongoDB is evaluated in a sharded and non-sharded environment.

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