1.apache / superset
Apache Superset is a Data Visualization and Data Exploration Platform
Ranked by Attention Score: stars gained over the last 7 complete days
55 repositories by Attention Score · Oct 27, 2026 – Nov 2, 2026 (UTC)
Apache Superset is a Data Visualization and Data Exploration Platform
A reactive notebook for Python — run reproducible experiments, query with SQL, execute as a script, deploy as an app, and version with git. Stored as pure Python. All in a modern, AI-native editor.
Apache Spark - A unified analytics engine for large-scale data processing
Learn how to develop, deploy and iterate on production-grade ML applications.
Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
Incremental engine for long horizon agents 🌟 Star if you like it!
An orchestration platform for the development, production, and observation of data assets.
Free Course : Data, Machine Learning, Deep Learning and AI Engineering, the long way round: the math, the code, the systems and the security. 173 lessons, 166 runnable labs, no shortcuts. Free under CC BY-NC 4.0.
data load tool (dlt) is an open source Python library that makes data loading easy 🛠️
Prefect is a workflow orchestration framework for building resilient data pipelines in Python.
Open-source data movement for ELT pipelines and AI agents — from APIs, databases & files to warehouses, lakes, and AI applications. Both self-hosted and Cloud.
🪓 An orchestration engine for background tasks, AI agents, and durable workflows
BullMQ - Message Queue and Batch processing for NodeJS, Python, .NET, Elixir, Rust and PHP based on Redis or PostgreSQL
Python SQL Parser and Transpiler
Python Stream Processing
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
Apache Beam is a unified programming model for Batch and Streaming data processing.
The most widely used Python to C compiler
the portable Python dataframe library
Build data pipelines with SQL and Python, ingest data from different sources, add quality checks, and build end-to-end flows.
Connect APIs, remarkably fast. Free for developers.
Asynchronous Python framework for event-driven services. A thin client for Kafka, RabbitMQ, NATS, Redis and MQTT with full access to native broker features, plus AsyncAPI docs, in-memory tests and observability out of the box.
Turns Data and AI algorithms into production-ready web applications in no time.
🌊 Online machine learning in Python
Apache DataFusion Ballista Distributed Query Engine
H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
The Open Source Feature Store for AI/ML
Apache Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage/tracing and metadata. Runs and scales everywhere python does.
Elyra extends JupyterLab with an AI centric approach.
List of Data Science Cheatsheets to rule the world
🔩 Like builtins, but boltons. 250+ constructs, recipes, and snippets which extend (and rely on nothing but) the Python standard library. Nothing like Michael Bolton.
Event-driven networking engine written in Python.
Make Your Company Data Driven. Connect to any data source, easily visualize, dashboard and share your data.
macOS development environment setup: Easy-to-understand instructions with automated setup scripts for developer tools like Vim, Sublime Text, Bash, iTerm, Python data analysis, Spark, Hadoop MapReduce, AWS, Heroku, JavaScript web development, Android development, common data stores, and dev-based OS X defaults.
a little task queue for python
Python Streaming DataFrames for Kafka
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
Utils for streaming large files (S3, HDFS, gzip, bz2...)
A library for event sourcing in Python.
The idiomatic asyncio MQTT client
Out-of-Core hybrid Apache Arrow/NumPy DataFrame for Python, ML, visualization and exploration of big tabular data at a billion rows per second 🚀
Real-time monitor and web admin for Celery distributed task queue
📚 Parameterize, execute, and analyze notebooks
Apache Avro is a data serialization system.
CLI task management & automation tool
Distributed Stream Processing
This repository is a getting started guide to Singer.
Hopsworks - Data-Intensive AI platform with a Feature Store
ADAM is a genomics analysis platform with specialized file formats built using Apache Avro, Apache Spark, and Apache Parquet. Apache 2 licensed.
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 🗄️
A robust web archive analytics toolkit
Realistic synthetic events for testing, demos, and pipelines — streamed live or generated in bulk
A detective for your data. Zero-config data quality monitoring — works with dbt, Postgres, BigQuery, Snowflake. No YAML.
Data ingestion engine — Singer taps to Parquet in cloud buckets