root

ROOT came out of CERN to handle the data volumes particle physics produces, and it is still the workhorse there. It is a C++ framework for storing, processing, and visualizing enormous datasets, with histogramming, curve fitting, and statistical modeling built in. If you work with measurements at a scale that breaks normal tools, this was built for exactly that. LGPL-2.1, free, decades of development behind it.

The power comes with a real learning curve. ROOT is C++ first, has its own file format and idioms, and the build and install are non-trivial. Outside high-energy physics, a lot of its conventions feel alien, and for general analysis the modern Python stack (pandas, NumPy, Arrow, Polars) is friendlier and moves faster. ROOT has Python bindings, but you can feel that you are visiting a C++ world.

Use it if you are in physics or another field that already lives in ROOT, or if you specifically need its statistical and histogramming machinery on massive datasets. For everyday data work, reach for the Python tools instead. There is no paid tier and no vendor; support is the community forum and the issue tracker.

The catch is fit. ROOT is brilliant at the narrow, heavy job it was designed for and overkill for almost everything else. If you are not sure you need it, you probably do not.