- Polars, DuckDB, Pandas, Modin, Ponder, Fugue, Daft — which one is the best dataframe and SQL tool? https://kestra.io/blogs/2023-08-11-dataframes 2 comments programming
Linked pages
- Polars https://www.pola.rs/ 516 comments
- DuckDB - An in-process SQL OLAP database management system https://duckdb.org/ 350 comments
- Polars https://www.pola.rs/posts/company-announcement/ 166 comments
- Apache Arrow and the "10 Things I Hate About pandas" - Wes McKinney https://wesmckinney.com/blog/apache-arrow-pandas-internals/ 143 comments
- GitHub - kestra-io/kestra: Orchestration and automation platform to execute millions of scheduled and event-driven workflows declaratively in code and from the UI https://github.com/kestra-io/kestra 108 comments
- Dask | Scale the Python tools you love https://dask.org 86 comments
- GitHub - Eventual-Inc/Daft: Distributed DataFrame for Python designed for the cloud, powered by Rust https://github.com/Eventual-Inc/Daft 39 comments
- RAPIDS | GPU Accelerated Data Science http://rapids.ai/ 25 comments
- GitHub - pola-rs/polars: Dataframes powered by a multithreaded, vectorized query engine, written in Rust https://github.com/pola-rs/polars 23 comments
- GitHub - fugue-project/fugue: A unified interface for distributed computing. Fugue executes SQL, Python, and Pandas code on Spark, Dask and Ray without any rewrites. https://github.com/fugue-project/fugue 23 comments
- Apache Arrow | Apache Arrow https://arrow.apache.org/ 10 comments
- Productionizing and scaling Python ML workloads simply | Ray https://ray.io 9 comments
- A Grammar of Data Manipulation • dplyr https://dplyr.tidyverse.org/index.html 4 comments
- Pandas API on Spark — PySpark 3.3.2 documentation https://spark.apache.org/docs/latest/api/python/user_guide/pandas_on_spark/index.html 3 comments
- GitHub - modin-project/modin: Modin: Scale your Pandas workflows by changing a single line of code https://github.com/modin-project/modin 0 comments
- GitHub - vaexio/vaex: Out-of-Core hybrid Apache Arrow/NumPy DataFrame for Python, ML, visualization and exploration of big tabular data at a billion rows per second 🚀 https://github.com/vaexio/vaex 0 comments
- GitHub - ibis-project/ibis: the portable Python dataframe library https://github.com/ibis-project/ibis 0 comments
- GitHub - dbt-labs/dbt-core: dbt enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications. https://github.com/dbt-labs/dbt-core 0 comments
- GitHub - Rdatatable/data.table: R's data.table package extends data.frame: https://github.com/Rdatatable/data.table 0 comments
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