Alternative to
6 Alternatives to Astronomer in 2026
Teams look beyond Astronomer when they do not want their pipelines tied to Airflow Dags, when hourly deployment billing is hard to budget, or when they need orchestration for application code and not only data jobs. Typical destinations are Kestra, Temporal, Mage, Windmill, Orchestra and AWS Step Functions.
Why people look for an alternative to Astronomer
Everything is built around Airflow
Astronomer hosts Airflow, so the Dag is the unit of work. Teams that would rather describe flows in YAML, write plain scripts or model long-running application logic have to bend their thinking to fit that shape.
Deployment hours and token fees stack up
Astronomer bills each deployment by the hour, adds separate worker sizes, charges extra for dedicated clusters, and meters its Otto agent per million tokens. A busy month is hard to forecast from the plan name alone.
Key controls sit behind quote-only tiers
Single sign-on, 90-day audit logs and the 1-hour support SLA start at Business, while custom RBAC, SCIM and remote execution agents start at Enterprise. Both tiers are quote only, so a small team that needs one control faces a sales process.
The best Astronomer alternatives
- 1
Kestra is a French-built orchestrator where workflows are declared in YAML and triggered by events, schedules or API calls. A large plugin catalog covers data, infrastructure and business tools, and the engine can be self-hosted from the open source edition or run as a hosted cloud service in an EU or US region.
Switch if you move off Python-only Dags toward declarative flows, and want a self-hosted engine with an EU region available.
- 2
Temporal treats a workflow as ordinary code in Go, Java, TypeScript, Python or .NET, and keeps its full state through crashes. That suits payments, onboarding and other long-lived processes more than scheduled data loads, and its Data Converter encrypts payloads before they leave your network.
Switch if you orchestrate long-running application logic that must survive failures, with retries and timers written in a general-purpose language.
- 3
Mage is a pipeline platform built around a notebook-style code editor with an AI assistant inside it. It ships streaming pipelines and Iceberg support, and a deployment can run in its cloud, in your private cloud or in a hybrid arrangement. Pricing combines a monthly tier with metered run time.
Switch if you want a smaller, editor-centered tool for building pipelines with AI help, and accept metered execution time instead of per-deployment hours.
- 4
Windmill turns scripts in Python, TypeScript, Go, Bash and SQL into endpoints, then chains them into flows with approvals and branches. A React or Svelte app builder sits on the same engine, so one self-hosted install can cover jobs, internal tools and agents.
Switch if you need scripts, workflows and small internal apps on one engine that your platform team hosts and controls.
- 5
Orchestra is a control plane aimed at dbt and Python teams, with lineage, a context catalog, data quality tests and YAML-defined agents in one view. It can also start jobs in tools such as Fivetran when new data lands, instead of owning the compute itself.
Switch if you mainly coordinate dbt runs and ingestion tools and want lineage and quality checks in the same screen without managing Airflow.
- 6
AWS Step Functions is Amazon's serverless state machine service, drawn as diagrams and wired straight into Lambda, Glue, ECS, SageMaker and other AWS services. There is no server to run, but the logic lives in AWS-specific definitions that do not travel to another cloud.
Switch if you already run most of your stack on AWS and prefer a managed service with no cluster over portable workflow code.
Before you switch away from Astronomer
Inventory what your Dags actually do before choosing a target. List the operators, sensors, connections and variables in use, and note which ones depend on Airflow providers that another engine will not have. Export your schedules, retry settings and alert routes, since each tool expresses them differently. Check where audit logs, secrets and SSO configuration live today and what the new vendor offers on the plan you would buy. Port one noncritical pipeline first, run it in parallel for a few weeks, and compare reliability and cost against your Astronomer invoice before cutting over the rest.
The full ranking of this category is in Best AI Data Orchestration Tools in 2026.
Frequently asked questions
Can I keep my Airflow Dags if I leave Astronomer?
Yes, if you stay on Airflow. Airflow is open source, so Dags can run on a self-managed cluster or another host. Moving to Kestra, Windmill, Mage or Step Functions means rewriting them in that tool's format, though Orchestra lists Airflow among the orchestrators it can work alongside, which eases a gradual move.
Which alternative is cheapest to start with?
Kestra and Windmill both offer open source editions you can self-host without a license fee, and Orchestra has a single-user free plan. Self-hosting still costs engineering time and infrastructure. Temporal and Step Functions bill by usage, so a light workload stays small but a high-volume one needs a real estimate first.
Do these tools handle compliance requirements better than Astronomer?
It varies. Astronomer's terms let you pick the cloud region and describe AES-256 and TLS 1.3 encryption, but its own SOC 2 report is not stated. Kestra states a SOC 2 Type 2 audit and GDPR compliance, Temporal Cloud states SOC 2 Type II, GDPR and HIPAA, and Mage and Orchestra publish less on the pages checked.
Is Temporal a direct replacement for Astronomer?
Not really. Astronomer runs scheduled data pipelines written as Airflow Dags, while Temporal runs durable code workflows for applications, such as order processing or account provisioning. Some data teams use both. Pick Temporal when failures and long waits in business logic are the problem, not when you mainly need scheduled loads and dbt runs.