1.apache / superset
Apache Superset is a Data Visualization and Data Exploration Platform
- superset
- apache
- apache-superset
- data-visualization
- data-viz
- analytics
- +12 more
Ranked by Attention Score: stars gained over the last 90 complete days
75 repositories by Attention Score · Aug 5, 2026 – Nov 2, 2026 (UTC)
Apache Superset is a Data Visualization and Data Exploration Platform
The open source AI engineering platform for agents, LLMs, and ML models. MLflow enables teams of all sizes to debug, evaluate, monitor, and optimize production-quality AI applications while controlling costs and managing access to models and data.
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 Airflow - A platform to programmatically author, schedule, and monitor workflows
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 platform for the development, production, and observation of data assets.
data load tool (dlt) is an open source Python library that makes data loading easy 🛠️
The Data Engineering Cookbook
Python SQL Parser and Transpiler
🌊 Online machine learning in Python
Always know what to expect from your data.
Python ETL framework for stream processing, real-time analytics, LLM pipelines, and RAG.
The Open Source Feature Store for AI/ML
Turns Data and AI algorithms into production-ready web applications in no time.
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.
🐚 Python-powered shell. Full-featured, cross-platform and AI-friendly.
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.
Meltano: the declarative code-first data integration engine that powers your wildest data and ML-powered product ideas. Say goodbye to writing, maintaining, and scaling your own API integrations.
the portable Python dataframe library
Lightweight and extensible compatibility layer between dataframe libraries!
Luigi is a Python module that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization etc. It also comes with Hadoop support built in.
🔩 Like builtins, but boltons. 250+ constructs, recipes, and snippets which extend (and rely on nothing but) the Python standard library. Nothing like Michael Bolton.
☁️ Build multimodal AI applications with cloud-native stack
📚 Parameterize, execute, and analyze notebooks
Real-time monitor and web admin for Celery distributed task queue
Event-driven networking engine written in Python.
Python Stream Processing
Messaging library for Python.
Realistic synthetic events for testing, demos, and pipelines — streamed live or generated in bulk
GUI for ChatGPT API and many LLMs. Supports agents, file-based QA, GPT finetuning and query with web search. All with a neat UI.
Out-of-Core hybrid Apache Arrow/NumPy DataFrame for Python, ML, visualization and exploration of big tabular data at a billion rows per second 🚀
CLI task management & automation tool
Python Streaming DataFrames for Kafka
Karapace - Your Apache Kafka® essentials in one tool
Utils for streaming large files (S3, HDFS, gzip, bz2...)
Elyra extends JupyterLab with an AI centric approach.
pandas on AWS - Easy integration with Athena, Glue, Redshift, Timestream, Neptune, OpenSearch, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR, SecretManager, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON and EXCEL).
A library for event sourcing in Python.
Pandas, Polars, Spark, and Snowpark DataFrame comparison for humans and more!
Compare tables within or across databases
Python Stream Processing. A Faust fork
Clean APIs for data cleaning. Python implementation of R package Janitor
The idiomatic asyncio MQTT client
PySpark test helper methods with beautiful error messages
Reverse ETL for the code-first data stack
Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
Python Stream Processing
The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️
WebSocket and WAMP in Python for Twisted and asyncio
A lightweight opinionated ETL framework, halfway between plain scripts and Apache Airflow
A detective for your data. Zero-config data quality monitoring — works with dbt, Postgres, BigQuery, Snowflake. No YAML.
TensorFlowOnSpark brings TensorFlow programs to Apache Spark clusters.
Koalas: pandas API on Apache Spark
:truck: Agile Data Preparation Workflows made easy with Pandas, Dask, cuDF, Dask-cuDF, Vaex and PySpark
Jupyter magics and kernels for working with remote Spark clusters
pyspark methods to enhance developer productivity 📣 👯 🎉
ENIGMA HALFpipe is a user-friendly software that facilitates reproducible analysis of fMRI data
MLBox is a powerful Automated Machine Learning python library.
Pythonic tool for orchestrating machine-learning/high performance/quantum-computing workflows in heterogeneous compute environments.
Streaming reactive and dataflow graphs in Python
No description provided by the repository host.
Blazingly fast data comparison tool for Python, powered by Rust. Compare massive CSV/Parquet datasets instantly.
Conflict-free merge for DataFrames, JSON, ML models & distributed agents — powered by CRDTs. The first merge library where every operation is mathematically guaranteed to converge.
Data ingestion engine — Singer taps to Parquet in cloud buckets
Crossbar.io - WAMP application router
PySpark + Scikit-learn = Sparkit-learn
AthenaCLI is a CLI tool for AWS Athena service that can do auto-completion and syntax highlighting.
Read and write Neuroglancer datasets programmatically.
🎲 Dotflow turns an idea into flow! — Lightweight Python library for execution pipelines