Polars
Polars is a high-performance DataFrame library implemented in Rust with bindings for Python, Node.js, and Rust. It is designed for fast data processing and analysis, leveraging multi-threading, SIMD, and lazy evaluation to handle large datasets efficiently. It provides a pandas-like API but with significant performance improvements, especially for out-of-core operations and complex queries.
Developers should learn Polars when working with large-scale data processing tasks where pandas becomes slow or memory-intensive, such as in data engineering, analytics, or machine learning pipelines. It is ideal for scenarios requiring high-speed filtering, aggregations, joins, and transformations on datasets that exceed memory limits, offering a seamless alternative with better scalability and performance.