Quick comparison # App Pricing Verified price Open source Platforms Verified facts Score 1 PrefectOpen source $100/month Yes Web, Linux, macOS +2 5 of 5 68.8 2 DagsterOpen source $10/month plus credits Yes Web, Linux, macOS +2 5 of 5 64.8 3 Argo WorkflowsOpen source — Yes Self-hosted 4 of 4 57.5 4 WindmillOpen source — Yes Web, Self-hosted 4 of 4 51.2 5 FlyteOpen source — Yes Self-hosted 4 of 4 42.3 6 TemporalOpen source $50 per million actions No Web, Self-hosted 5 of 5 42.3
1 Best for: Python teams who want orchestration without rewriting code into a separate DAG framework
Open source Self-hostable Web, Linux, macOS, Windows, Self-hosted
Why switch from Apache Airflow
Turns ordinary Python functions into workflows with one decorator, with a free hosted tier to skip running servers.
Pros Plain Python with a decorator, little new to learn Free hosted Hobby tier and a self-hostable open source server Runs on your own compute, Kubernetes or serverlessCons Free cloud tier is limited to 2 users and 5 deployments Smaller integration ecosystem than Airflow Paid plans jump quickly from a flat fee to per-user pricingHow this score is calculated Editorial fit ×0.3 100
Reviews ×0.3 63
Clicks (90 days) ×0.15 0
Freshness ×0.15 100
Votes ×0.1 50
0 counted reviews, 0 up and 0 down votes. Full formula
2 Best for: Data platform teams who want lineage, data quality and orchestration in one tool
Open source Self-hostable Web, Linux, macOS, Windows, Self-hosted
Why switch from Apache Airflow
Asset-centric orchestration with built-in lineage and better local testing for data platform teams.
Pros Asset-based model makes lineage and freshness visible Strong local development and testing workflow Close dbt integration Hybrid deployment keeps data in your own cloudCons Asset-centric model takes time to learn if you think in tasks Managed plans add usage-based credits on top of the monthly fee No free hosted tier beyond the trialHow this score is calculated Editorial fit ×0.3 87
Reviews ×0.3 63
Clicks (90 days) ×0.15 0
Freshness ×0.15 100
Votes ×0.1 50
0 counted reviews, 0 up and 0 down votes. Full formula
3 Best for: Platform teams already on Kubernetes who want container-native batch and ML pipelines.
Open source Self-hostable Self-hosted
Why switch from Apache Airflow
Kubernetes-native workflow engine where each step runs as a container, a fit for teams already running everything on K8s.
Pros Free, Apache 2.0 licensed CNCF project Any language works, since each step is a container Handles large parallel jobs on Kubernetes Python users can define workflows with HeraCons Requires a Kubernetes cluster YAML definitions get verbose for data engineers used to Python No hosted version from the project itselfHow this score is calculated Editorial fit ×0.3 63
Reviews ×0.3 63
Clicks (90 days) ×0.15 0
Freshness ×0.15 100
Votes ×0.1 50
0 counted reviews, 0 up and 0 down votes. Full formula
4 Best for: Engineering teams that want scripts, workflows and internal UIs in one self-hosted platform
Open source Self-hostable Web, Self-hosted
Why switch from Apache Airflow
Open source scripts, flows and internal UIs in one self-hosted tool, with a lighter setup than Airflow.
Pros Scripts, workflows and apps in one place Supports many languages including Python and TypeScript Free self-hosted edition with unlimited executionsCons Built for developers, not business users App builder is less polished than Retool's Enterprise features need a paid licenceHow this score is calculated Editorial fit ×0.3 41
Reviews ×0.3 63
Clicks (90 days) ×0.15 0
Freshness ×0.15 100
Votes ×0.1 50
0 counted reviews, 0 up and 0 down votes. Full formula
5 Best for: ML and data teams on Kubernetes who want typed, reproducible Python pipelines.
Open source Self-hostable Self-hosted
Why switch from Apache Airflow
Typed Python tasks with caching and resumable runs, built for ML pipelines on Kubernetes.
Pros Free and Apache 2.0 licensed Typed task inputs and outputs catch errors early Caching and retries resume from the failed step Managed option through Union.aiCons Needs a Kubernetes cluster for production use Flyte 2 changes the SDK, so Flyte 1 code needs migrating Smaller community than AirflowHow this score is calculated Editorial fit ×0.3 12
Reviews ×0.3 63
Clicks (90 days) ×0.15 0
Freshness ×0.15 100
Votes ×0.1 50
0 counted reviews, 0 up and 0 down votes. Full formula
6 Best for: Engineering teams building business-critical, long-running processes in several languages
Open source Web, Self-hosted
Why switch from Apache Airflow
Durable execution for application workflows that need retries and long waits, not just scheduled DAGs.
Pros MIT-licensed server you can run anywhere Official SDKs for eight languages Handles retries, timers and long waits without custom state machines Detailed per-workflow event history for debuggingCons Steep learning curve, including rules about deterministic workflow code You still run and scale your own worker processes Self-hosting the cluster and its database is a significant ops jobHow this score is calculated Editorial fit ×0.3 12
Reviews ×0.3 63
Clicks (90 days) ×0.15 0
Freshness ×0.15 100
Votes ×0.1 50
0 counted reviews, 0 up and 0 down votes. Full formula
Verified facts 5 of 5 verified Free credits $150 for 90 days Checked Nov 8, 2026temporal.io(opens source in a new tab) Starting price $50 per million actions Checked Nov 8, 2026temporal.io(opens source in a new tab) SDK languages Go, Java, Python, TypeScript, .NET, PHP, Ruby, Rust Checked Nov 8, 2026temporal.io(opens source in a new tab)