#Arrow
Showing 50 of 50 repositories tagged #arrow, ranked by stars
Extremely fast Query Engine for DataFrames, written in Rust
cuDF - GPU DataFrame Library
🏹 Better dates & times for Python
Apache DataFusion SQL Query Engine
The perfect companion for your Kotlin journey - Inspired by functional, data-oriented and concurrent programming
High-performance data engine for AI and multimodal workloads. Process images, audio, video, and structured data at any scale
Official Rust implementation of Apache Arrow
Create full-fledged APIs for slowly moving datasets without writing a single line of code.
LakeSoul is an end-to-end, realtime cloud-native Lakehouse framework for fast data ingestion, concurrent updates, incremental analytics, multimodal data processing and vector search — powering next-generation BI and AI workloads.
Drop-in Apache Spark replacement written in Rust, unifying batch processing, stream processing, and compute-intensive AI workloads.
An extensible, state-of-the-art framework for columnar compression, and the fastest FOSS columnar file format. Formerly at @spiraldb, now an Incubation Stage project at LFAI&Data, part of the Linux Foundation.
Apache DataFusion Ballista Distributed Query Engine
BlazingSQL is a lightweight, GPU accelerated, SQL engine for Python. Built on RAPIDS cuDF.
The Auron accelerator for distributed computing framework (e.g., Spark) leverages native vectorized execution to accelerate query processing
Tonbo is an embedded database for serverless and edge runtimes.
Ergonomic bindings to duckdb for Rust
Nice and simple customizable implementation of Google style up/down expand arrow.
Rust-based WebAssembly bindings to read and write Apache Parquet data
Multi-Modal Database replacing MongoDB, Neo4J, and Elastic with 1 faster ACID solution, with NetworkX and Pandas interfaces, and bindings for C 99, C++ 17, Python 3, Java, GoLang 🗄️
DataFusion has now been donated to the Apache Arrow project
High-performance analytical database. 19.9M records/sec ingestion, 8.4M+ rows/sec queries. Ingestion, compaction, SQL, retention, continuous queries — one binary. Open Parquet on your storage. S3/Azure native. Air-gap ready. No vendor lock-in. AGPL-3.0.
Data Preview 🈸 extension for importing 📤 viewing 🔎 slicing 🔪 dicing 🎲 charting 📊 & exporting 📥 large JSON array/config, YAML, Apache Arrow, Avro, Parquet & Excel data files
Unified MySQL, Postgres & FlightSQL Server, Powered by DuckDB.
Polars R bindings
Executable memory system for tabular data work
🏹 Parse JSON with style
Unofficial rust implementation of Apache Iceberg with integration for Datafusion
A fast excel reader for Rust and Python
Blazing-Fast Bioinformatic Operations on Python DataFrames
A data science toolkit for the H3 geospatial grid
🦖 A SQL-on-everything Query Engine you can execute over multiple databases and file formats. Query your data, where it lives.
Jetpack Compose + Kotlin + Coroutines + Koin + Coil + Klock + Spotless + Ktlint + Detekt + MVVM + MVI
A high-performance data streaming system using DuckDB and Apache Arrow Flight.
A set of tools for writing servers that speak PostgreSQL's wire protocol
A Streamlit component to render interactive Vega, Vega-Lite, and Altair visualizations and access the selected data from Python
Fast, minimal, and ergonomic zero-copy Apache Arrow tabular data implementation in Rust, with PyO3, Python bindings, shared-memory and low-latency SIMD for data-engineering and columnar workloads. Bridge to Polars and Arrow-rs over FFI effortlessly.
Kalidation = A Kotlin validation DSL
Data streaming runtime focused on performance, consistency, and extensibility. Write plugins in Rust or WASM and process data with data guarantees.
Kotlin Multiplatform Error Handling. Catch and handle all errors. Avoid Crashes. Like Arrow but without the black magic. No boilerplate. No performance overhead. 90+ operators.
Monads composition API that just works. For OOP developers
Vinum is a SQL processor for Python, designed for data analysis workflows and in-memory analytics.
Awesome list of alternative dataframe libraries in Python.
Notes on Data Engineering with Pandas, PySpark, Dask, Ray, Arrow DataFusion, Polars etc.
A simple yet powerful SDK for the YouTube Analytics API.
A high-performance Python Kafka client. Efficiently from Kafka to Pandas and back.
A high-performance spatial query layer for Polars
Go data analysis / manipulation library built on top of Apache Arrow
High-speed PII masking as a Polars plugin — powered by Rust
Rust-native time-series table format with gap/overlap tracking and SQL queries
JupyterLab Notebook for Mesosphere DC/OS