For workflow orchestration triggers, the strongest matches are conductor-oss/conductor (Conductor is a comprehensive workflow orchestration platform that provides), langflow-ai/langflow (Langflow is a visual, low-code workflow orchestration platform designed) and apache/incubator-airflow (Apache Airflow is a comprehensive workflow orchestration platform that). temporalio/temporal and sentient-agi/roma round out the shortlist. Each is ranked by relevance to your query, popularity and recent activity.
Compare the top workflow orchestration engines. We ranked the best open-source tools by activity and features to help you find the right fit.
Conductor is a durable workflow engine designed to orchestrate complex, long-running business processes and autonomous agent loops. It functions as a stateful execution platform that persists the entire history of a process, ensuring that workflows remain reliable and recoverable across infrastructure failures, system restarts, and transient network errors. By managing task lifecycles, worker polling, and state transitions, it provides a centralized coordination layer for distributed systems. The platform distinguishes itself through its specialized support for AI agent orchestration, allowin
Conductor is a comprehensive workflow orchestration platform that provides distributed task execution, state persistence, and event-driven automation, making it a flagship solution for managing complex, long-running business processes.
Langflow is a visual interface for building and orchestrating workflows, allowing users to construct complex systems through a drag-and-drop canvas. It provides tools for managing autonomous agents, configuring memory settings, and integrating custom code-based components. Users can organize their work into projects, track component versions, and group multiple elements into reusable units. The platform includes an interactive playground for testing workflows, monitoring tool calls, and debugging chat sessions with unique identifiers. Once built, workflows can be executed via RESTful or OpenA
Langflow is a visual, low-code workflow orchestration platform designed for building and executing complex AI agent systems, though it is more specialized for LLM-based automation than general-purpose task scheduling.
This project is a Python workflow orchestration platform and programmatic data pipeline engine used to author, schedule, and monitor complex data pipelines. It functions as a directed acyclic graph manager and scheduler, allowing users to define data movement and transformation tasks as code to ensure precise execution order and maintainability. The platform distinguishes itself by treating workflows as code, enabling pipelines to be versioned and tested through a standard programming language. It utilizes a system of extensible operators to encapsulate integration logic and employs a templat
Apache Airflow is a comprehensive workflow orchestration platform that natively supports DAG-based scheduling, distributed task execution, and state persistence, making it a flagship solution for complex pipeline automation.
Temporal is a distributed workflow orchestration engine designed to manage fault-tolerant, stateful, and long-running background processes. It functions as a platform for coordinating complex cross-service operations, ensuring consistency and reliability in distributed environments by decoupling workflow orchestration from task execution. The platform distinguishes itself through a deterministic, event-sourced execution model that reconstructs workflow state by re-executing code from an immutable event log. This approach isolates non-deterministic side effects into managed activities, allowin
Temporal is a robust, distributed workflow orchestration engine that excels at managing complex, long-running, and stateful processes through an event-sourced execution model, making it a flagship solution for event-driven and scheduled automation.
ROMA is an agentic workflow engine and recursive task orchestrator designed to coordinate autonomous agents in the execution of complex workflows. It functions as a multi-agent framework that decomposes high-level goals into atomic subtasks and manages their execution through a dependency graph. The system distinguishes itself through a hierarchical plan-execute loop that recursively decomposes objectives and synthesizes results from leaf-node tasks upward. It ensures execution purity via atomic task isolation, assigning dedicated storage directories to individual tasks to prevent data interf
ROMA is a workflow orchestration engine that manages complex task execution through dependency graphs and state persistence, making it a suitable tool for orchestrating agentic workflows even if it focuses more on recursive decomposition than traditional DAG-based scheduling.
Metaflow is a Python machine learning framework and MLOps workflow orchestrator designed to manage the lifecycle of data pipelines from local prototyping to production. It serves as a distributed compute manager and an experiment tracking system, enabling the creation of reproducible pipelines that transition between development and high-availability production environments. The framework distinguishes itself through an integrated checkpointing system that automatically persists intermediate data artifacts to remote storage, allowing failed runs to be resumed from the last successful step. It
Metaflow is a workflow orchestration platform specifically designed for data science and machine learning pipelines, offering distributed task execution, state persistence, and DAG-based scheduling that fits the core requirements for complex task management.
Kestra is a declarative workflow orchestrator designed to manage complex task dependencies and automated processes through versioned configuration files. It functions as a distributed platform that decouples task scheduling from execution by offloading computational workloads to a fleet of worker nodes. The system uses a reactive, event-driven engine to initiate workflows automatically in response to external signals, webhooks, schedules, or file system changes. The platform distinguishes itself through a modular plugin architecture that allows for the integration of custom tasks and external
Kestra is a comprehensive workflow orchestration platform that natively supports event-driven triggers, DAG-based scheduling, and distributed task execution, making it a complete solution for complex automation needs.
n8n is a workflow automation platform that combines a visual interface with code-based extensibility to design, orchestrate, and manage automated processes. It provides a comprehensive suite of tools for data transformation, filtering, and storage, allowing users to build complex logic through conditional branching, looping, and sub-workflow execution. The platform supports both pre-built integration nodes and custom code execution in JavaScript or Python, enabling connectivity with a wide range of external services and APIs. The platform includes a suite of generative AI capabilities, such a
n8n is a comprehensive workflow orchestration platform that provides a visual builder, event-driven triggers, and robust state persistence, making it a flagship solution for managing complex, distributed automated processes.
Airflow is a platform for programmatically authoring, scheduling, and monitoring complex data pipelines. It functions as a workflow automation engine that manages the lifecycle of recurring business processes by executing code-defined task dependencies. By representing workflows as directed acyclic graphs, the system ensures that task execution order and data flow are explicitly defined and reliably maintained across distributed computing environments. The platform distinguishes itself through a highly modular, provider-based architecture that decouples core orchestration logic from external
Airflow is a comprehensive workflow orchestration platform that uses DAGs for scheduling and supports distributed task execution, making it a flagship tool for managing complex, code-defined automation pipelines.
Argo Workflows is a container-native workflow engine that functions as a Kubernetes custom resource controller. It orchestrates complex sequences of containerized tasks by executing them as directed acyclic graphs, allowing for dependency management and parallel processing within a cluster. The system extends the native Kubernetes control plane to manage the full lifecycle of automated processes, from initial triggering to final resource cleanup. The platform distinguishes itself through its controller-pattern reconciliation, which continuously monitors workflow states to align them with desi
Argo Workflows is a container-native engine that provides robust DAG-based scheduling, distributed task execution on Kubernetes, and event-driven automation, making it a comprehensive solution for complex workflow orchestration.
Dagster is a data orchestration platform designed to manage the entire lifecycle of data assets through declarative modeling and version-controlled code. It functions as a workflow engine that treats data assets as first-class primitives, allowing teams to define, schedule, and monitor complex pipelines while maintaining clear visibility into lineage, dependencies, and data quality. The platform distinguishes itself by using a code-as-configuration framework that enables standard software engineering practices, such as unit testing and local mocking, to be applied directly to data workflows.
Dagster is a comprehensive workflow orchestration platform that natively supports DAG-based scheduling, distributed execution, and event-driven data pipelines, making it a flagship solution for complex task management.
DolphinScheduler is a distributed workflow orchestrator designed to manage and automate complex data processing pipelines. It functions as a data pipeline scheduler that coordinates multi-step tasks across distributed environments, ensuring reliable execution through defined dependencies and sequences. The platform utilizes a directed acyclic graph model to represent workflows, allowing users to define task relationships via a visual interface. It employs a master-worker architecture supported by a pluggable task plugin system, which enables the dynamic extension of task types without requiri
DolphinScheduler is a comprehensive workflow orchestration platform that provides a visual DAG-based builder, distributed task execution, and robust state persistence, making it a direct fit for complex event-driven and scheduled automation.
Conductor is a distributed workflow manager and microservices orchestration engine. It coordinates long-running business processes across a network of services, using a stateful orchestration model to ensure consistent execution order and reliable state management. The system defines task sequences and conditional business logic using structured JSON configuration files. It manages the execution of complex operations across distributed systems with built-in persistence and failure recovery, tracking the progress of processes through a backend database. The platform provides capabilities for
Conductor is a robust, distributed workflow orchestration engine that natively supports complex DAG-based task scheduling, state persistence, and reliable execution across microservices, making it a comprehensive solution for your automation needs.
Camunda is a business process automation platform and orchestration tool used to model, deploy, and monitor automated workflows and human-centric tasks. It features a BPMN workflow engine for executing processes based on the BPMN 2.0 standard and a DMN decision engine for automating business logic and rule evaluation. The platform is designed for flexibility through an embedded workflow library that allows the engine to be integrated directly into custom applications. It supports multi-tenant workflow management, enabling the secure separation of process definitions and instance data for mult
Camunda is a comprehensive workflow orchestration platform that provides a robust BPMN engine for complex task scheduling, distributed execution, and state persistence, making it a flagship solution for event-driven business process automation.
Argo is a cloud native CI/CD platform and Kubernetes workflow engine. It functions as a container pipeline orchestrator and job scheduler, managing multi-step sequences of containers as jobs using directed acyclic graphs within a cluster. The system acts as a progressive delivery controller, reducing release risk through automated Canary and Blue-Green deployment strategies. It provides declarative GitOps synchronization to mirror the state of a git repository directly into the cluster environment for continuous delivery automation. The platform covers a broad range of capabilities including
Argo is a comprehensive Kubernetes-native workflow orchestration engine that natively supports DAG-based scheduling, event-driven triggers, and distributed task execution, making it a flagship solution for complex automation.
ClaraVerse is a self-hosted orchestration platform for deploying and managing local language models, autonomous agents, and automated workflows on private infrastructure. It functions as a containerized backend manager that orchestrates services, databases, and model providers within local containers to maintain data sovereignty. The platform features a visual workflow builder with a drag-and-drop interface for designing complex parallel task sequences. It utilizes a multi-model abstraction layer to normalize interactions across diverse local and remote AI endpoints and includes a retrieval a
ClaraVerse is a self-hosted orchestration platform that provides a visual workflow builder and backend service management, making it a suitable tool for designing and executing automated task sequences.
Polyaxon is a Kubernetes-native machine learning orchestration platform and MLOps pipeline orchestrator. It serves as a control plane for managing distributed deep learning workloads, automated machine learning pipelines, and experiment tracking. The platform distinguishes itself through specialized services for distributed training management, including MPI-based coordination for PyTorch and TensorFlow. It provides an automated hyperparameter optimization service utilizing Bayesian, random, and grid search algorithms, alongside managed interactive AI workspaces for launching Jupyter notebook
Polyaxon is a Kubernetes-native platform designed for orchestrating machine learning pipelines and distributed workloads, providing the necessary DAG-based scheduling and task execution capabilities for complex automation tasks.
OpenWhisk is a serverless cloud platform designed for deploying and executing stateless functions in response to API calls or events. It serves as a complete serverless stack, providing an API gateway for functions, a function-as-a-service runtime manager, and an event-driven workflow engine. The platform distinguishes itself through a polyglot execution model that supports multiple language runtimes and allows for the creation of custom runtimes using Docker containers. It enables complex logic through function orchestration and composition, allowing multiple functions to be chained into seq
OpenWhisk is a serverless platform that provides event-driven triggers and distributed task execution, functioning as an orchestration engine for chaining stateless functions into complex workflows.
Hatchet is an open-source durable workflow engine and task orchestration platform. It provides a framework for building and executing fault-tolerant, multi-step pipelines as directed acyclic graphs (DAGs), with automatic retries, scheduling, and real-time observability. The system is built around durable task checkpointing, which persists execution state after each step so work can resume from the last checkpoint after a worker crash or restart, and it supports event-driven task resumption that pauses a task until a matching external event arrives. The platform distinguishes itself through it
Hatchet is a durable workflow orchestration engine that natively supports DAG-based scheduling, distributed task execution, and event-driven triggers, making it a strong fit for complex automation needs despite lacking a built-in visual workflow builder.
Azkaban is a distributed workflow manager and DAG-based job orchestrator designed as an enterprise batch processor. It serves as a Java-based workflow engine that schedules and executes complex job sequences across a cluster of executor servers, with specific functionality for managing big data workloads on Hadoop clusters. The system distinguishes itself through a distributed executor model that coordinates state via a shared database to ensure high availability. It employs a plugin-based architecture that allows for custom job types and system functionality extensions, including the ability
Azkaban is a distributed, DAG-based workflow orchestrator that supports complex job scheduling and event-driven triggers, making it a robust engine for managing enterprise-scale data pipelines.
This project is an AI agent orchestration platform that provides a visual environment for building, testing, and deploying complex automation workflows. It functions as a low-code development interface where users can chain discrete functional blocks into dependency-aware pipelines to integrate artificial intelligence with external data and services. The platform supports the creation of intelligent conversational agents, automated business processes, and multi-service API orchestrations within a unified workspace. The platform distinguishes itself through its event-driven integration engine,
This platform provides a visual, low-code environment for building dependency-aware automation pipelines and event-driven workflows, making it a suitable tool for orchestrating complex tasks and AI-integrated processes.
AutoGPT is an orchestration platform designed for building, managing, and deploying autonomous agents. It provides a visual canvas-based environment where users can assemble agents by connecting modular blocks that represent actions, data flows, and conditional logic. The platform supports the entire agent lifecycle, including task scheduling, execution monitoring, and configuration management, while offering a marketplace for discovering and sharing community-built workflows. The project includes a legacy framework for command-line agent execution and an extensible component system for devel
AutoGPT provides a visual, canvas-based environment for orchestrating autonomous agents through modular workflows, task scheduling, and event-driven triggers, fitting the core requirements of a workflow orchestration platform.
Osmedeus is a security workflow orchestration engine that coordinates AI agents, shell commands, and scanning tools through declarative YAML pipelines. It functions as a distributed security scanner, a declarative workflow automator, and an AI agent framework for security, enabling automated multi-step security analysis with conditional branching, parallel execution, and distributed workers. The engine distinguishes itself through a hybrid runner model that executes workflow steps on the local host, inside Docker containers, or over SSH to remote machines, selected per step or module. It supp
Osmedeus is a workflow orchestration engine specifically tailored for security automation, providing distributed task execution and YAML-based pipeline management that fits the core requirements for complex task scheduling.
ZenML is an extensible machine learning orchestration framework designed to manage the end-to-end lifecycle of data pipelines and AI agent workflows. It functions as a durable orchestrator that executes machine learning tasks as directed acyclic graphs, ensuring that every step is containerized for consistent performance across local, cloud, and hybrid infrastructure. By decoupling pipeline code from underlying compute and storage backends, the platform allows developers to define infrastructure-agnostic stacks that remain portable across diverse environments. The project distinguishes itself
ZenML is a workflow orchestration framework specifically designed for machine learning pipelines that utilizes DAG-based scheduling and distributed execution, making it a strong fit for complex task orchestration despite its specialized focus on data and AI workflows.
Elsa Core is a workflow engine framework designed for defining, executing, and managing long-running business processes. It functions as a distributed workflow orchestrator and event-driven trigger system, capable of operating as a multi-tenant platform with secure data isolation. The project distinguishes itself through a flexible approach to workflow definitions, supporting a visual drag-and-drop designer, programmatic C# definitions, and portable JSON specifications. It provides a highly extensible architecture allowing for the development of custom activities and the use of a dynamic expr
Elsa Core is a workflow orchestration framework that provides event-driven triggers, distributed execution, and a visual designer, making it a robust engine for managing complex business processes.
OpenManus is an autonomous agent framework designed to build intelligent software entities capable of executing complex, multi-step tasks through independent decision-making. It functions as a workflow orchestration engine that uses a central language model to interpret user goals, break them down into actionable steps, and manage the execution flow of agents. The system maintains coherence across tasks through a stateful execution context that tracks progress and intermediate data. The platform distinguishes itself through a dynamic capability discovery mechanism that inspects tool definitio
OpenManus is an agent-based orchestration framework that manages complex, multi-step task execution and stateful workflows, making it a specialized tool for autonomous automation rather than a traditional DAG-based scheduling engine.
Mastra is an orchestration framework designed for building, deploying, and managing autonomous AI agents and multi-agent systems. It provides a comprehensive suite of primitives for creating resilient AI applications, including durable workflow orchestration, event-driven agent loops, and semantic memory management. By integrating these core components, the platform enables developers to build complex, multi-step processes that can reason about goals and execute tasks without manual intervention. The framework distinguishes itself through its focus on observability and secure, isolated execut
Mastra is a workflow orchestration framework specifically designed for managing complex, stateful AI agent processes, offering the event-driven triggers and durable execution required for modern automation tasks.
Archon is an artificial intelligence agent automation engine designed to orchestrate complex development workflows. It functions as a platform for chaining multi-step tasks into directed graphs, allowing developers to standardize and execute repeatable coding patterns through declarative configuration files. The system distinguishes itself by maintaining stateful context across long-running sessions and executing operations within isolated, containerized worktrees to prevent file interference. It integrates with external language models and provides a centralized registry for sharing and inst
Archon is a workflow orchestration engine that uses directed acyclic graphs to manage stateful, containerized task execution, making it a suitable tool for complex automation despite its specific focus on AI-driven development workflows.
Celery is an asynchronous job processor and distributed task queue designed to offload time-consuming operations to background worker nodes. By utilizing a message-passing architecture, it decouples task producers from consumers, allowing applications to maintain responsiveness while scaling workloads across multiple isolated environments. The system functions as a distributed workload orchestrator that manages the lifecycle of deferred operations through persistent queues. It distinguishes itself by providing a pluggable transport abstraction, which allows the core task logic to remain indep
Celery is a distributed task queue and job processor that provides the core infrastructure for task scheduling and execution, though it functions as a library for building workflows rather than a standalone platform with a built-in visual builder.
CrewAI is a multi-agent orchestration framework designed for building autonomous systems that execute complex, multi-step workflows. It provides a development platform where specialized agents are defined with specific roles, goals, and tool sets to perform tasks collaboratively. By leveraging a declarative workflow engine, the system manages task dependencies, state transitions, and execution logic, allowing for the creation of structured, stateful sequences of operations. The framework distinguishes itself through its hierarchical management capabilities, which utilize manager agents to coo
CrewAI is a framework for orchestrating autonomous AI agents that manages complex task dependencies and stateful workflows, making it a specialized tool for event-driven and multi-step automation.
Prefect is a workflow orchestration platform designed to define, schedule, and monitor complex data pipelines as Python code. It functions as a container-native engine that wraps individual tasks in isolated environments, ensuring consistent dependencies and resource allocation across diverse infrastructure. By utilizing a state-machine-based orchestration model, the system tracks execution progress through discrete transitions and persistent event logs to maintain reliable and observable task processing. The platform distinguishes itself through a decoupled worker-API architecture, which sep
Prefect is a robust workflow orchestration engine that provides distributed task execution, state persistence, and DAG-based scheduling through Python-defined pipelines, though it focuses on code-first orchestration rather than a visual workflow builder.
Luigi is a Python framework designed for building and managing complex batch data pipelines. It functions as a workflow orchestration engine that organizes tasks into directed acyclic graphs, ensuring that jobs execute in the correct logical order based on their dependencies. By utilizing a centralized scheduler, the system coordinates task execution across distributed environments, tracks global workflow state, and prevents redundant processing by verifying the existence of output targets before triggering any work. The project distinguishes itself through a robust state-tracking mechanism t
Luigi is a robust workflow orchestration engine that excels at managing complex DAG-based data pipelines with distributed task execution and state persistence, though it lacks a built-in visual workflow builder.
Kedro is a data science pipeline framework and orchestration tool designed to build reproducible and modular data engineering workflows. It functions as an MLOps project template and Python data workflow tool that enforces software engineering best practices to move projects from prototype to production. The system distinguishes itself through a centralized data catalog manager that abstracts data access and versioning across various file formats and cloud storage systems. It further separates processing logic from data access via a lazy-loading data registry and provides a standardized proje
Kedro is a Python-based framework for building modular, DAG-based data pipelines that supports complex task scheduling and dependency resolution, though it is more focused on data engineering workflows than general-purpose event-driven automation.
Flyte is a Kubernetes-based machine learning orchestrator and containerized pipeline manager designed for coordinating AI workflows and data pipelines. It functions as an engine for defining and executing resilient pipelines, utilizing a data lineage tracker to maintain immutable execution states and ensure reproducible outputs. The platform distinguishes itself by packaging individual tasks into separate containers to ensure dependency isolation and environment consistency. It provides specialized capabilities for machine learning, including the transformation of trained models into scalable
Flyte is a robust workflow orchestration engine that supports DAG-based scheduling, distributed task execution, and event-driven triggers, making it a strong fit for complex pipeline automation despite its specific focus on data and machine learning workflows.
Apache NiFi is a flow-based programming platform that enables the visual design, monitoring, and management of data pipelines. At its core, it provides a web-based visual dataflow designer where users build directed graphs of processors to route, transform, and mediate data movement between any source and destination without writing custom code. The system records fine-grained data provenance for every data item from ingestion to delivery, supporting audit, debugging, and replay of data lineage. The platform distinguishes itself through a zero-master cluster architecture that distributes proc
Apache NiFi is a visual, flow-based orchestration platform that excels at managing complex data movement and pipeline automation, though it focuses more on data-centric routing than general-purpose task scheduling.
Mirror of Apache Oozie
Apache Oozie is a mature workflow orchestration engine designed for Hadoop ecosystems that supports DAG-based scheduling and distributed task execution, though it lacks a modern visual builder and native event-driven triggers.
The rp-engine is a workflow orchestration framework designed for building and executing autonomous agentic tasks. Built in Rust, it provides a structured environment for managing complex, multi-step operations that integrate language models with external tools and data sources. The engine distinguishes itself through its native support for iterative planning loops and persistent state management. By utilizing a directed acyclic graph architecture, it coordinates sequences of tasks while maintaining a shared memory bank that updates automatically to inform future steps. The system relies on de
This is a YAML-native workflow execution engine designed for agentic tasks, providing the core capability of distributed task orchestration even though it lacks a built-in visual builder.
Trigger.dev is a platform for building durable, event-driven background workflows. It functions as a workflow engine that allows developers to define complex, long-running processes using standard code rather than proprietary configuration languages. By utilizing a durable execution model, the system checkpoints progress, ensuring that tasks can automatically resume from the exact point of failure after a crash or interruption. The platform distinguishes itself through its focus on stateful, multi-step automation and real-time feedback. It supports the orchestration of AI agents and external
Trigger.dev is a workflow orchestration platform that provides event-driven triggers, distributed task execution, and durable state persistence, making it a strong fit for building complex, long-running automated processes.
Core package for defining and running durable workflows and activities. Supports long-running persistent workflows, retries, queues, parallel execution, workflow monitoring, dedicated storage connections, and orchestration for microservices, data pipelines, sagas, agentic workflows, and other complex business processes.
This is a workflow orchestration engine designed for the PHP ecosystem that provides durable execution, state persistence, and support for complex business processes, though it lacks a built-in visual workflow builder.
Activiti is a workflow engine designed to model, execute, and manage business processes using the BPMN 2.0 standard. It functions as a Java-based framework that embeds process orchestration directly into enterprise applications and microservices to coordinate sequences of tasks and human-centric interactions. The platform utilizes a persistent state machine to maintain the status of long-running workflows in a relational database, ensuring continuity across system restarts. It manages high-volume environments through optimistic concurrency control, which tracks versioning tokens to prevent da
Activiti is a robust BPMN-based workflow engine that provides state persistence and event-driven orchestration for complex business processes, though it is primarily designed as a Java framework for embedding into applications rather than a standalone visual platform.
Semaphore is a centralized web-based platform designed for the orchestration and execution of Ansible automation. It provides a unified control plane to manage infrastructure operations, allowing teams to organize inventories, environment variables, and playbooks into reusable templates. The platform supports multi-tenant governance by isolating resources into projects, ensuring clear separation between different teams and infrastructure segments. The system distinguishes itself through a distributed task runner architecture that offloads automation workloads to independent nodes, enabling sc
Semaphore is a workflow orchestration platform specifically tailored for managing and executing Ansible playbooks, providing distributed task execution and scheduling capabilities that align with your requirements for infrastructure automation.
Inngest is a durable execution framework and event-driven automation engine designed to orchestrate background workflows. It enables developers to build resilient, stateful processes by memoizing function steps, ensuring that long-running tasks can automatically resume from the last successful operation after failures, timeouts, or infrastructure restarts. The platform distinguishes itself through its event-driven architecture, which uses a schema-validated bus to trigger functions and coordinate complex, multi-step logic. It employs an onion-model middleware approach for cross-cutting concer
Inngest is a durable execution framework that provides event-driven triggers and stateful workflow orchestration, making it a strong fit for building resilient, distributed background processes.
Activepieces is an open-source, self-hosted workflow automation platform designed to connect third-party applications through modular triggers and actions. It provides a low-code integration framework that allows users to build, manage, and execute complex business logic sequences within isolated, sandboxed environments. The platform distinguishes itself through its focus on embeddability and enterprise-grade security. It features an embedded automation builder that can be integrated into external applications via iframes, supported by comprehensive identity and access management tools such a
Activepieces is a self-hosted, low-code workflow automation platform that provides event-driven triggers and stateful execution, making it a capable engine for managing complex business logic and task sequences.
Workflow is a platform for executing long-running, stateful processes that automatically persist progress and recover state after system interruptions. It functions as a durable orchestration engine designed to manage complex, multi-step asynchronous operations within distributed systems. The framework distinguishes itself through event-sourcing and checkpointing mechanisms that record execution steps as an immutable log, allowing for precise state reconstruction after failures. It provides sandboxed task isolation to run side-effect-heavy logic in restricted environments, ensuring that sensi
This is a durable workflow orchestration engine that provides state persistence and distributed task execution, though it lacks a built-in visual workflow builder.
| Dépôt | Stars | Langage | Licence | Dernier push |
|---|---|---|---|---|
| conductor-oss/conductor | 32K | Java | Apache-2.0 | |
| langflow-ai/langflow | 149.7K | Python | MIT | |
| apache/incubator-airflow | 45.8K | Python | Apache-2.0 | |
| temporalio/temporal | 18.4K | Go | mit | |
| sentient-agi/roma | 5.1K | Python | — | |
| netflix/metaflow | 9.8K | Python | apache-2.0 | |
| kestra-io/kestra | 27.1K | Java | Apache-2.0 | |
| n8n-io/n8n | 192.8K | TypeScript | NOASSERTION | |
| apache/airflow | 45.9K | Python | Apache-2.0 | |
| argoproj/argo-workflows | 16.5K | Go | apache-2.0 |