Open-source Azure Logic Apps alternatives

n8n is a workflow automation platform for connecting apps, moving data between them and triggering actions without writing a full integration from scratch. Workflows are built on a visual canvas, and when a step needs more logic you can drop in JavaScript or Python and use npm packages. It is often compared with Zapier and Make, but the source is public and it can run on your own infrastructure.

Recent versions put a lot of weight on AI. You can build multi-step agents and LLM workflows that call OpenAI, Anthropic, Google or open-source models, add human approval steps, and inspect what happened afterward. The project advertises over a thousand integrations and a large library of ready-made workflow templates, and you can extend it with your own nodes.

n8n is distributed under a fair-code model: the Sustainable Use License, plus a separate enterprise license for additional features. The code is always visible and can be self-hosted, for example with Docker, but it is not an OSI-approved open-source license, so commercial redistribution is restricted. A managed cloud edition is available if you would rather not run it yourself.

Conductor is an event-driven workflow engine that makes microservice and AI agent execution durable. It treats choices made at runtime, including loops, branches, parallel fan-out, tool calls, approval steps, retries and cancellation, as durable, inspectable executions. The project began at Netflix and is now maintained by Orkes and the community. It is written in Java with a JavaScript UI and released under the Apache-2.0 license.

Every step is persisted, so a workflow can continue after a crash, a restart or a network outage, and retries and timeouts are configurable. Orchestration is kept as a versioned graph while workers and built-in tasks perform the business logic. For AI use, it provides native LLM tasks, MCP tool calling, human approval steps and vector workflows for retrieval-augmented generation. A quickstart needs Node.js and Java 21 or later, serves a UI on port 8080, and a Docker image is also available.

Kestra is an orchestration platform, open source, for data pipelines, AI workflows and infrastructure automation. It brings scheduled and event-triggered automation together under one declarative interface that does not depend on a programming language, applying infrastructure-as-code practices to pipelines so that reliable workflows can be defined in a few lines of YAML.

Workflows can be built in the UI, written by a built-in AI Copilot, or generated from coding agents such as Claude Code and Cursor using agent skills, and everything can be kept as code with Git integration even when it was authored visually. A large plugin ecosystem connects it to external systems, and key concepts cover tasks, triggers and flows. The project is written in Java, with topics covering orchestration, high availability, pipeline-as-code and DevOps, and the 2.0 release adds new capabilities.

Kestra is Apache-2.0 licensed and can be self-hosted, with a quick start that gets a first workflow running in minutes. It targets data engineers, platform teams and automation developers who want an alternative to schedulers such as Airflow with a more declarative style.

Activepieces is an open-source replacement for Zapier, positioned as an all-in-one AI automation tool. Automations are built from pieces, which are type-safe TypeScript npm packages, and the interface is meant to work for both technical and non-technical users. The topics also describe it as an alternative to n8n. The repository metadata lists the license as Other.

Pieces that are contributed to the project automatically become available as MCP servers, so LLM clients such as Claude Desktop, Cursor and Windsurf can use them. The platform includes native AI pieces for working with different providers, an AI SDK for building agents inside the builder, and human-in-the-loop steps that delay execution or require approval. Developers can set up tools, then others in the organization use the no-code builder. It can be self-hosted, including in network-gapped environments, and supports branding customization.

Node-RED is a low-code programming tool for event-driven applications built on flow-based, visual programming. Instead of writing everything as code, you connect nodes that represent inputs, processing steps and outputs, which makes it popular for IoT projects, home automation and wiring together APIs and online services. It is a project of the OpenJS Foundation.

Getting started takes a couple of commands: install it globally with npm, start it with the node-red command, and open it in your browser. A large ecosystem sits around it, with a library of custom nodes and integrations, shared flows and node collections, plus documentation, a forum and a Slack community. Developers can also run the latest code from git by cloning the repository, installing dependencies and building it.

Node-RED is written in JavaScript on Node.js and licensed under Apache-2.0. You run it on your own computer, a Raspberry Pi, a server or in a container, so there is no hosted service to depend on. It suits makers, integrators and engineers who want to prototype and automate event-driven logic quickly.

Temporal is a durable execution platform that helps developers create scalable applications while keeping both productivity and reliability. The Temporal server runs units of application logic called Workflows, handling intermittent failures and retrying failed operations automatically. It started as a fork of Uber's Cadence and is developed by Temporal Technologies, a company founded by Cadence's creators. The server is written in Go and released under the MIT license.

This repository contains the source of the server only. To implement Workflows, Activities and Workers you use one of the supported language SDKs. The getting started guide shows how to download and run a pre-built image with its dependencies locally, try samples written for Go or Java, interact with the server through the Temporal CLI, and watch workflows in the Web UI at port 8233. Repository topics cover workflow engines, distributed cron, microservice orchestration and durable execution.

Windmill is an open-source platform for developers to run internal code as APIs, background jobs, workflows and user interfaces. It is pitched as a self-hostable alternative to Retool, Pipedream and Superblocks and as a simplified version of Temporal, and it automatically generates UIs so a script can be shared and triggered as an internal app.

Scripts can be written in languages including Python, TypeScript, Go, Bash, SQL, PowerShell, Rust and GraphQL. They can be composed into flows or used within richer apps built with its low-code builder. The backend is written in Rust on PostgreSQL, and the README describes it as a very fast self-hosted workflow engine, citing a comparison with Airflow. Sections of its documentation cover main concepts, local development, architecture, security, performance and self-hosting with Docker Compose.

Windmill is open source under AGPLv3, and Windmill Labs sells dedicated instances, commercial support and licenses, so the repository license is listed as 'Other' on GitHub. It suits engineering teams that want to turn existing scripts into reliable internal tools and automations without building each interface by hand.

Zato is an open-source platform written in Python for integration, automation and orchestration. It lets organizations connect business systems, APIs, workflows and even hardware assets, and is described as an enterprise service bus and API platform for service-oriented architectures.

The project lists industries such as airports, defense, health care, telecommunications, financial services and government, and its topics mention API gateway, FHIR, HL7 interoperability, low-code and iPaaS. The README is short and points to the project website for downloads, screenshots and programming examples.

Zato is licensed under AGPL-3.0 and is installed on your own infrastructure. The homepage could not be retrieved when this entry was prepared, so detailed deployment and pricing information should be checked on the project site. It suits integration engineers who prefer to write integration logic in Python.

ByteChef is an open-source platform that brings AI agents and workflow automation into one product. It can be self-hosted or embedded inside a SaaS application, and it is presented as an alternative to tools like Zapier and n8n, with a drag-and-drop workflow editor for building automations across APIs.

An AI Agent component runs the full agent loop of model, tool selection, execution and observation as a step in a durable workflow, so a failed or paused run resumes from that step. The README lists support for many LLM providers such as OpenAI, Anthropic, Azure OpenAI, Bedrock, Mistral, Groq, DeepSeek and Ollama, components that double as agent tools, several memory backends, and guardrails. Topics also mention MCP, embedded iPaaS and Workato-style integrations.

The core is licensed under Apache 2.0 according to the README, while the repository metadata lists the licence as other. ByteChef is written in Java and TypeScript, with an embedded edition for shipping the same agents in your own product, plus documentation, templates and a connector developer guide. It suits engineering teams that want automation and agents under their own control.

Apache Camel Karavan is a low-code data integration platform that simplifies the Apache Camel experience by letting teams design integration microservices visually and deploy them quickly. It aims to give the full power of Apache Camel through a visual tool, from low-code use cases to pro-code projects, drawing on more than ten years of community experience.

The designer supports Enterprise Integration Patterns, over 300 integration components, a REST API designer with an OpenAPI to REST DSL generator, YAML for integrations with Java for custom code, a route designer and a topology view. The deployer provides shell scripts for building and deploying and predefined customizable configurations for different platforms, and a developer dashboard offers hot reload, live logs and tracing of exchange data. Architecturally, the Karavan app manages projects, a build container packages and runs integrations, a Git repository stores project files as the source of truth, and an image registry holds built container images.

A VS Code extension provides a local developer experience for designing and running integrations on a laptop and deploying to Kubernetes or OpenShift. The platform can be installed on Docker, Kubernetes or OpenShift, is part of the Apache Software Foundation and is licensed under Apache-2.0.