Big data often associates with significant computational and programming effort. This is not always the case. In many cases, we can make sense of our data for much less resource, provided that we know what we are doing. Our goal is to provide a library that supports data summarization on the fly.


You can summarize and visualize your data or data streams on the fly with many updates per seconds for little to no resource.


The library provides plug-and-play analysis tools for big data. Advanced tools to handle graphs and sets will also be provided.

Provable guarantee

Algorithms are backed up by sublinear algorithms, data mining, and machine learning literature.