Open-source Boomi 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.

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.

Mirth Connect, from NextGen Healthcare, is an integration engine for healthcare data. The README likens it to an interpreter: when a foreign system sends a message, Connect translates the message standard into the one your own system understands. Project topics point to HL7 and interoperability, and the software is written in Java.

Its message processing steps include filtering, which reads message parameters and decides whether a message continues to transformation, transformation, which converts one standard to another such as HL7 to XML, extraction, which can pull data from and push data to a database, and routing to the appropriate destination systems. These steps let organizations connect applications that use different formats.

The README covers useful links to downloads, a user guide, a wiki with an FAQ, forums and a Slack channel, followed by sections on installation, upgrading, starting the server and running on Java 9 or later. It includes a Java licensing note and a license section. The latest release listed is 4.5.2, and NextGen frames the product as supporting everything from small practices to large health information exchanges.

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.

Titanoboa is a workflow orchestration platform that runs on the JVM and is designed to be distributed, scalable and fault tolerant. Workflows can be built with low-code tooling and extended with Java, Kotlin or Clojure, with Python support described as coming. It can run on-premises or in the cloud, on bare metal, virtual machines, Docker or Kubernetes.

The engine supports sequential and parallel steps, configurable retries with custom error handling, branching, conditional flow and even cyclic workflow graphs. Splitter and aggregator patterns allow larger data sets to be processed, steps are transactional so they complete even through a failover, and new workflows can be developed and deployed at runtime. Clustering can scale to many nodes, with no central master server or database.

The README lists use cases including big data and data pipeline automation, orchestrating microservices, acting as an iPaaS or integration platform, ETL, IT automation, an enterprise service bus and batch processing. Titanoboa is released under AGPL-3.0, and its design draws on immutability and functional programming principles. A wiki and predefined workflow steps are available.