Mage OSS
Best for self-hosting
Why teams pick it
Teams requiring self-hosted, on-premises data orchestration
Open-source alternatives to Dagster
Compare community-driven replacements for Dagster in workflow orchestration tools workflows. We curate active, self-hostable options with transparent licensing so you can evaluate the right fit quickly.
Dagster
Dagster is an open‑source orchestrator for data assets and jobs with typed IO, schedules, sensors, and a web UI for observability.Read more
Key stats
- 15Alternatives
- 3Support self-hosting
Run on infrastructure you control
- 12Active development
Recent commits in the last 6 months
- 11Permissive licenses
MIT, Apache, and similar licenses
Counts reflect projects currently indexed as alternatives to Dagster.
Start with these picks
These projects match the most common migration paths for teams replacing Dagster.
Prefect
Privacy-first alternative
Why teams pick it
Keep customer data in-house with privacy-focused tooling.
All open-source alternatives
SciPipe
Fast, flexible Go library for building robust scientific pipelines
Permissive licenseIntegration-friendlyAI-powered workflowsGo
Why teams choose it
- Intuitive flow‑based programming model using Go channels
- Seamlessly wrap any command‑line tool alongside native Go processes
- Compiled to fast binaries with built‑in parallel and task‑level concurrency
Watch for
Requires familiarity with Go programming
Migration highlight
Genome variant calling pipeline
Orchestrates alignment, sorting, and annotation tools with parallel execution, producing reproducible results and audit logs.
Dagster
Cloud-native orchestrator for developing and maintaining data assets
Active developmentPermissive licenseIntegration-friendlyPython
Why teams choose it
- Declarative asset definitions using Python functions with automatic dependency resolution
- Integrated lineage tracking, observability, and cataloging in a unified control plane
- Built-in testability supporting local development through production deployment
Watch for
Python-centric approach may require learning curve for non-Python teams
Migration highlight
Machine Learning Pipeline Orchestration
Define feature tables, training datasets, and models as assets with automatic dependency tracking and lineage from raw data to deployed models
Prefect
Pythonic workflow engine for resilient, observable data pipelines
Active developmentPermissive licensePrivacy-firstPython
Why teams choose it
- Pythonic decorators for flows and tasks
- Built‑in scheduling, retries, and caching
- Unified UI for monitoring and debugging
Watch for
Limited to the Python ecosystem
Migration highlight
Daily ETL job
Automates extraction, transformation, and loading of data each night with retries and monitoring.
Mage OSS
Build modern data pipelines locally with visual, modular code
Self-host friendlyActive developmentPermissive licensePython
Why teams choose it
- Modular notebook UI for Python, SQL, and R pipeline development
- Prebuilt connectors to databases, APIs, and cloud storage
- Visual debugging with live data previews and step-by-step logs
Watch for
Advanced orchestration and AI features require Mage Pro upgrade
Migration highlight
Google Sheets to Snowflake ETL
Automate data extraction from Google Sheets, apply Python transformations, and load results into Snowflake on a daily schedule.
Apache Airflow
Programmatically author, schedule, and monitor workflows as code
Active developmentPermissive licenseIntegration-friendlyPython
Why teams choose it
- Code-based DAG authoring with dynamic generation and parameterization
- Rich web UI for visualizing pipelines, monitoring progress, and troubleshooting
- Extensible operator library with Jinja templating for customization
Watch for
Not designed for streaming or high-volume data transfer between tasks
Migration highlight
ETL Pipeline Orchestration
Coordinate extraction, transformation, and loading across databases, data warehouses, and cloud storage with dependency-aware scheduling and retry logic.
Nextflow
Scalable, portable, reproducible pipelines powered by dataflow programming
Active developmentPermissive licenseFast to deployGroovy
Why teams choose it
- Dataflow DSL simplifies parallel pipeline definition
- Runs on local, HPC, cloud batch services, and Kubernetes
- Native support for Docker, Singularity, Conda, Spack, Podman
Watch for
Learning curve for the Nextflow DSL and Groovy syntax
Migration highlight
Genome variant calling at scale
Run a reproducible variant‑calling pipeline on local, SLURM, or AWS Batch without rewriting code.
Maestro
Scalable workflow orchestrator powering Netflix’s data platform
Active developmentPermissive licenseFast to deployJava
Why teams choose it
- Fully managed workflow‑as‑a‑service (WAAS)
- Handles hundreds of thousands of workflows and millions of jobs daily
- Highly scalable and extensible for new use cases
Watch for
Requires Java 21, Gradle, and Docker for operation
Migration highlight
ETL pipeline automation
Streamlines daily data extraction, transformation, and loading across hundreds of jobs
Polaris
Lightweight Go workflow orchestrator for payments and fulfillment
Integration-friendlyAI-powered workflowsGo
Why teams choose it
- Automatic step sequencing with concurrent execution
- Built‑in pause/resume when required data is missing
- Reusable builder components for shared logic
Watch for
Limited to Go ecosystem; not language‑agnostic
Migration highlight
Card payment processing
Orchestrates initiation, encryption, tokenization, OTP verification, and invoice generation in a single reusable workflow.
Orchest
Visual, code‑first data pipelines without YAML or frameworks
Self-host friendlyPermissive licensePrivacy-firstTypeScript
Why teams choose it
- Drag‑and‑drop UI for building pipelines
- Write pipeline steps directly in Python, R, or Julia notebooks or scripts
- Run jobs on demand or on a schedule with custom environments
Watch for
No longer actively maintained; future updates uncertain
Migration highlight
Train and compare regression models
Iterate on multiple models within a single visual pipeline, tracking performance and code versions.
Kestra
Event-Driven Declarative Orchestration Platform for Modern Workflows
Active developmentPermissive licenseFast to deployJava
Why teams choose it
- Declarative YAML workflows with built-in UI editor, auto-completion, and Git integration
- Event-driven triggers for Kafka, SQS, Pub/Sub, file systems, and custom events
- Execute scripts in any language (Python, Node.js, R, Go, Shell) on Docker or Kubernetes
Watch for
YAML-based configuration may require learning curve for teams unfamiliar with declarative syntax
Migration highlight
Event-Driven Data Pipelines
Automatically trigger ETL workflows when new files arrive in S3 or messages land in Kafka, processing data in real-time without manual intervention.
Apache DolphinScheduler
Modern, low-code platform for high-performance data workflow orchestration
Active developmentPermissive licenseFast to deployJava
Why teams choose it
- Four deployment modes: Standalone, Cluster, Docker, Kubernetes
- Drag-and-drop Web UI plus Python SDK and Open API
- Decentralized multi-master/worker architecture with horizontal scaling
Watch for
Java‑centric codebase may steepen learning curve for non‑Java teams
Migration highlight
ETL pipeline orchestration across hybrid clouds
Automates data extraction, transformation, and loading across AWS, GCP, and on-premise clusters with versioned workflows and fail-over handling.
Dagu
Lightweight workflow engine with declarative YAML and Web UI
Active developmentFast to deployIntegration-friendlyGo
Why teams choose it
- Single binary installation with zero external dependencies or databases
- Declarative YAML workflows wrapping shell scripts, SSH commands, and Docker
- Built-in Web UI for visualizing DAGs, logs, and execution control
Watch for
Designed for small-to-medium projects; may lack enterprise-scale features
Migration highlight
Migrating Legacy Cron Jobs
Visualize implicit dependencies between hundreds of cron scripts and manage reruns through a Web UI instead of SSH sessions.
Inngest
Durable step functions that replace queues and scheduling
Active developmentPrivacy-firstIntegration-friendlyGo
Why teams choose it
- Multi‑language SDKs for TypeScript, Python, Go, and Kotlin/Java
- Fine‑grained flow control (concurrency, throttling, debouncing, rate limiting)
- Automatic step retries with persistent state storage
Watch for
Requires integration of Inngest SDKs into existing code
Migration highlight
User‑specific image processing pipeline
Processes and resizes uploaded images per user with concurrency limits, automatically retrying failed steps.
Conductor
Scalable orchestration engine for resilient microservice workflows
Active developmentPermissive licenseFast to deployJava
Why teams choose it
- Workflow as code with JSON versioning
- Rich task catalog (HTTP, Lambda, Sub‑workflow, Event)
- Built‑in UI for monitoring and debugging
Watch for
Requires Java 17+ runtime
Migration highlight
Order fulfillment pipeline
Coordinates inventory check, payment processing, shipping label creation, and notification across services with automatic retries on failures.
Windmill
Self-hosted platform to turn scripts into internal apps
Self-host friendlyActive developmentPrivacy-firstHTML
Why teams choose it
- Auto‑generated UI from script parameters
- Multi‑language support: Python, TypeScript, Go, Bash, SQL, GraphQL
- Fast, sandboxed execution engine with nsjail isolation
Watch for
Self‑hosting requires operational knowledge of Docker/Kubernetes
Migration highlight
Ad‑hoc data extraction
A Python script pulls data from a database, UI lets analysts run it on demand, and results are saved back to Postgres.
Choosing a workflow orchestration tools alternative
Teams replacing Dagster in workflow orchestration tools workflows typically weigh self-hosting needs, integration coverage, and licensing obligations.
- 3 projects let you self-host and keep customer data on infrastructure you control.
- 12 options are actively maintained with recent commits.
Tip: shortlist one hosted and one self-hosted option so stakeholders can compare trade-offs before migrating away from Dagster.