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.
The Open Context Layer for Data and AI , OpenMetadata is the open platform for building trusted data context and business semantics for humans, AI assistants, and agents.
🦎 A lightweight, streaming-native, multi-protocol gateway for AI, APIs, and real-time data. Route LLM requests across providers, govern MCP tools, and connect Kafka, MQTT, and HTTP through one high-performance engine with shared security and observability.
Self-hostable workflow orchestrator for teams whose main work isn't orchestration. Declarative YAML over your scripts, SSH commands, containers, etc; keep workflows separate from business logic. One binary, no database, runs on limited H/W resources. Alternative to Airflow / Cron / Job Scheduler.
Open-source ETL/ELT you deploy on your own servers or cloud. Built on DuckDB: no-code/low-code visual pipelines or SQL, 385 components, dbt, CDC, data quality, reverse ETL, lineage, MCP for AI agents. No vendor cloud, no per-row billing.
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.
Convert documents to structured data effortlessly. Unstructured is open-source ETL solution for transforming complex documents into clean, structured formats for language models. Visit our website to learn more about our enterprise grade Platform product for production grade workflows, partitioning, enrichments, chunking and embedding.
Scalable real-time messaging server in a language-agnostic way. Self-hosted alternative to Pubnub, Pusher, Ably, socket.io, Phoenix.PubSub, SignalR. Set up once and forever.
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.
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.
An open-source storage framework that enables building a Lakehouse architecture with compute engines including Spark, PrestoDB, Flink, Trino, and Hive and APIs
Apache Camel is an open source integration framework with 350+ connectors. Write routes in Java, YAML, or XML. Run on Spring Boot, Quarkus, or standalone. Apache License 2.0.
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.
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.
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.
High performance Node.js/PostgreSQL job queue (also suitable for getting jobs generated by PostgreSQL triggers/functions out into a different work queue)