They both are open source distributed time series databases, OpenTSDB for metrics, InfluxDB for metrics and events with no external dependencies, on the other OpenTSDB based on HBase.
Any other comparation between them?
And if I want to store and query|analyze metrics real-time with no deterioration loss based on time series, which would be better?
At one of the conferences I've heard people running something like Graphite/OpenTSDB for collecting metrics centrally and InfluxDB locally on each server to collect metrics only for this server. (InfluxDB was chosen for local storage as it is easy to deploy and lightweight on memory).
This is not directly related to your question but the idea appealed to me much so I wanted to share it.
Warp 10 is another option worth considering (I'm part of the team building it), check it out at http://www.warp10.io/.
It is based on HBase but also has a standalone version which will work fine for volumes in the low 100s billions of datapoints, so it should fit most use cases out there.
Among the strengths of Warp 10 is the WarpScript language which is built from the ground up for manipulating (Geo) Time Series.
Yet another open-source option is blueflood: http://blueflood.io.
Disclaimer: like Paul Dix, I'm biased by the fact that I work on Blueflood.
Based on your short list of requirements, I'd say Blueflood is a good fit. Perhaps if you can specify the size of your dataset, the type of analysis you need to run or any other requirements that you think make your project unique, we could help steer you towards a more precise answer. Without knowing more about what you want to do, it's going to be hard for us to answer more meaningfully.
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