Vaex in one line: Vaex is Pandas with lazy evaluation and memory mapping.
Vaex is a data wrangling Python library. It helps developers work with “uncomfortably large” datasets on a single machine using lazy evaluation, memory mapping, and integrations with C++ code. It’s specifically designed to work “out of core” – to process data that’s too big to be loaded into memory (RAM) all at once.
Pandas is a popular, high-level library for handling tabular data, but it often has efficiency issues. Both Python and Pandas value simplicity over efficiency, and Python code in particular is often difficult to properly parallelize because of the GIL.
Vaex solves this problem by rebuilding a Pandas-like library “from the ground up,” taking advantage of lower-level C++ integrations for parallelization and lazy evaluation. Opening a 100GB dataset on a normal laptop is difficult with Pandas, but Vaex can do this efficiently, allowing developers to analyze larger datasets without compute clusters.