Python ETL framework for stream processing, real-time analytics, LLM pipelines, and RAG.
- batch-processing
- kafka
- pathway
- python
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Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
- airflow
- apache
- apache-airflow
- python
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
Parallel computing with task scheduling
- dask
- python
- pydata
- numpy
1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.
- pandas-profiling
- pandas-dataframe
- statistics
- jupyter-notebook
Out-of-Core hybrid Apache Arrow/NumPy DataFrame for Python, ML, visualization and exploration of big tabular data at a billion rows per second 🚀
- dataframe
- python
- bigdata
- tabular-data
The Open Source Feature Store for AI/ML
- machine-learning
- features
- ml
- big-data
🌊 Online machine learning in Python
- incremental-learning
- machine-learning
- python
- online-learning
TensorFlowOnSpark brings TensorFlow programs to Apache Spark clusters.
Python Stream Processing
- python
- stream-processing
- rust
- data-engineering
Elyra extends JupyterLab with an AI centric approach.
- notebooks
- notebook-jupyter
- jupyterlab
- jupyterlab-extensions
Python Streaming DataFrames for Kafka
Distributed Deep learning with Keras & Spark
:truck: Agile Data Preparation Workflows made easy with Pandas, Dask, cuDF, Dask-cuDF, Vaex and PySpark
MLBox is a powerful Automated Machine Learning python library.
- machine-learning
- auto-ml
- kaggle
- deep-learning
PySpark + Scikit-learn = Sparkit-learn
Pythonic tool for orchestrating machine-learning/high performance/quantum-computing workflows in heterogeneous compute environments.
- hpc
- workflow
- workflow-automation
- workflow-management
The world's cleanest AutoML library ✨ - Do hyperparameter tuning with the right pipeline abstractions to write clean deep learning production pipelines. Let your pipeline steps have hyperparameter spaces. Design steps in your pipeline like components. Compatible with Scikit-Learn, TensorFlow, and most other libraries, frameworks and MLOps environments.
- pipeline
- pipeline-framework
- machine-learning
- deep-learning
BatchFlow helps you conveniently work with random or sequential batches of your data and define data processing and machine learning workflows even for datasets that do not fit into memory.
- python3
- data-science
- machine-learning
- python
Build and deploy a serverless data pipeline on AWS with no effort.
- aws-cdk
- data-pipeline
- stepfunctions
- glue
Stream Processing Made Easy
- machine-learning
- reactive-programming
- kafka
- reactive-systems
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.
- collaborative-editing
- conflict-resolution
- crdt
- data-engineering