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I'm looking for a time series database that can be easily used with Python and Pandas objects such as DataFrame, Panel...

But these objects will always contains time series.

Ideally I'm looking for an open source database.

I want this TSDB able to manage ticks data.

2 millions rows should be processed (stored and retrieved) in less than 30 seconds.

What do you suggest? What are the pros and cons of each?

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OpenTSDB is good for large-scale time series storage. metrilyx/opentsdb-pandas and wiktorski/opentsdb_pandas seems to provide the interface with pandas. OpenTSDB and HBase rough performance test | MoreDevs provides a benchmark, may not exactly match your requirements but you can try.

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There is a times series DBMS (InfiniFlux) that can be easily used with Python.

The database is not open source but it does provide a free version for evaluation, too. So you can try whether the DBMS is suitable for your project.

You are asking 2M rows should be processed in less than 30 seconds, InfiniFlux can store and retrieve more than 500,000 data within a second. In addition, it provide standard SQL and interface.

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  • $\begingroup$ Please not that the poster is associated with the product. $\endgroup$
    – Bob Jansen ♦
    Commented May 23, 2017 at 18:23

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