Grizzlars
Developer ProductivityA high‑performance Python DataFrame library backed by a multithreaded C++ engine for fast, low‑memory data manipulation
Features
- Multithreaded C++ core enables parallel operations across all CPU cores
- Consumes up to ~6× less memory than Polars when loading large CSVs
- Python API with typed columns stored as native std::vector buffers (no GIL overhead)
- Supports standard DataFrame actions: sort, filter, groupby, join, aggregation
- Built‑in I/O helpers (`read_csv`, `to_csv`) that leverage the native multithreaded reader/writer
Recent releases
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Install & Platforms
Install via
pip
Platforms
linux
macos
windows
Similar tools
Alternative to
Polars