Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
- airflow
- apache
- apache-airflow
- python
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Orchestrate everything, everywhere. The open-source control plane for workflows across data, infrastructure, business processes and AI agents. Declarative YAML, event-driven, any language, Git-versioned, scalable to millions of executions.
- orchestration
- data-orchestration
- high-availability
- infrastructure-as-code
Prefect is a workflow orchestration framework for building resilient data pipelines in Python.
An orchestration platform for the development, production, and observation of data assets.
- data-pipelines
- dagster
- workflow
- data-science
Always know what to expect from your data.
- pipeline-tests
- dataquality
- datacleaning
- datacleaner
Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable, and modular.
- kedro
- hacktoberfest
- mlops
- python
Build, Manage and Deploy AI/ML Systems
- machine-learning
- model-management
- ai
- ml
Fancy stream processing made operationally mundane
- message-queue
- stream-processing
- streaming-data
- message-bus
Evidently is an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.
- data-drift
- jupyter-notebook
- pandas-dataframe
- machine-learning
Zero-ETL, infinite possibilities. Live query APIs, code & more with SQL. No DB required.
- steampipe
- postgresql
- postgresql-fdw
- cloud
The Open Source Feature Store for AI/ML
- machine-learning
- features
- ml
- big-data
Data pipelines for cloud config and security data. Build cloud asset inventory, CSPM, FinOps, and vulnerability management solutions. Extract from AWS, Azure, GCP, and 70+ cloud and SaaS sources.
ZenML 🙏: One AI Platform from Pipelines to Agents. https://zenml.io.
- mlops
- machine-learning
- data-science
- production-ready
Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling to thoroughly test your data and models from research to production.
- machine-learning
- ml
- model-validation
- data-validation
AI Infra / AI Orchestration / AI Control Plane
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.
- dataops
- dataops-platform
- elt
- open-source
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.
- data-science
- python
- dag
- data-engineering
Tenzir is the data pipeline engine for security teams.
- incident-response
- threathunting
- siem
- soc
Data Quality and Observability platform for the whole data lifecycle, from profiling new data sources to full automation with Data Observability. Configure data quality checks from the UI or in YAML files, let DQOps run the data quality checks daily to detect data quality issues.
- data-ops
- data-quality
- data-quality-checks
- data-quality-measurement
Realistic synthetic events for testing, demos, and pipelines — streamed live or generated in bulk
- clickhouse
- data-engineering
- data-generation
- devops
Stream Ops is a fully embeddable data streaming engine and stream processing API for Java.
Open, audit-grade agentic data quality framework with portable industry packs