Open Source C++ Data Analytics Tools

DuckDB is a high-performance analytical database system. It is designed to be fast, reliable and easy to use. DuckDB provides a rich SQL dialect, with support far beyond basic SQL. DuckDB supports arbitrary and nested correlated subqueries, window functions, collations, complex types (arrays, structs), and more. For more information on the goals of DuckDB, please refer to the Why DuckDB page on our website. Processing and storing tabular datasets, e.g. from CSV or Parquet files. Interactive data analysis, e.g. Joining & aggregate multiple large tables. Concurrent large changes, to multiple large tables, e.g. appending rows, adding/removing/updating columns. Large result set transfer to client. For development, DuckDB requires CMake, Python3 and a C++11 compliant compiler. Run make in the root directory to compile the sources. For development, use make debug to build a non-optimized debug version.

StarRocks is the next generation of real-time SQL engines for enterprise analytics. Real-time analytics is notoriously difficult. Complex data pipelines and de-normalized tables have always been a necessary evil. Processing any updates or deletes once data arrives has not been possible- until now. StarRocks solves these challenges and makes real-time analytics easy. Get amazing query performance on Star or Snowflake Schemas directly. From canceled orders to updated items, your analytics applications can easily handle them with StarRocks. From streaming data to change data capture, StarRocks meets the data ingestion demands of real-time analytics. Scale storage and computing power horizontally and support tens of thousands of concurrent users. All of your BI tools work with StarRocks through standard SQL. StarRocks provides superior performance. It is also a unified OLAP covering most data analytics scenarios.

A collection of tools for working with the comparative data analysis ontology including import/export facilities for common phylogenetic file formats, and also a triple-store framework.

KeplerDB is a temporal database to store time/value entries where the type of value could be integer, float/double, boolean and string. KeplerDB is dedicated to be scalable and to create clusters of server allowing the user to analyse and store massing amount of data to monitor systems like computers, clusters, building and captors or financial systems like markets and accounts. The user can use KeplerDB to make data analysis on enormous amount of data (statistics and modelling).

MathROOT is a tool for high-energy physicists to access the ROOT data analysis framework from within Mathematica