A Rust-backed Bloomberg client with Python and Node.js bindings for reference, historical, intraday, streaming and BQL data requests.
70364RustApache-2.0Well maintainedUpdated 19 hours ago
#arrow
Best open-source columnar DataFrame and query engines (2026)
These tools run queries and transformations over tabular data in columnar memory, which is often much faster than row-by-row code on large datasets. When choosing one, decide whether you need a drop-in replacement for an existing stack like pandas or Spark, or a new engine you call directly, and whether you have NVIDIA GPUs. polars is a fast Rust engine with Python, Node.js, R and SQL bindings. cudf runs pandas-style code on GPUs, often with no code changes. sail runs existing PySpark code over Spark Connect.
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6 repositories
A Python library that lets you query Xarray datasets with SQL by treating array data as tables, usable with DuckDB, Polars, DataFusion and ADBC engines.
153+2 this week24PythonApache-2.0Updated 22 hours ago
A fast DataFrame query engine written in Rust, with Python, Node.js, R, Rust and SQL bindings.
40.3K+37 this week3.2KRustMITUpdated 11 hours ago
GPU-accelerated DataFrame library for tabular data, with a pandas-like API and a zero-code-change pandas accelerator.
9.8K+9 this week1.2KC++Apache-2.0Updated 4 hours ago
A Spark accelerator that runs Spark SQL and DataFrame operators on Apache Arrow columnar data via a Rust engine built on DataFusion, with no code changes.
1.3K+7 this week414ScalaApache-2.0Updated 4 hours ago
A drop-in Apache Spark replacement written in Rust that runs existing PySpark code over the Spark Connect protocol.
3.5K+8 this week240RustApache-2.0Well maintainedUpdated 7 hours ago