7 Best Data Orchestration Software

Apache Airflow is the best data orchestration software for most teams, because it is free, open source and the most widely used orchestrator in the industry. Pipelines are defined as Python DAGs, which means a data engineer writes ordinary Python code with operators for AWS, Google Cloud, Azure, dbt, Spark and hundreds of other systems. The licence costs $0 under Apache 2.0, and the buyer pays only for the infrastructure and the engineer time to run it.

• The community is the largest in the category, so almost every integration and every failure mode has a documented answer.
• Airflow 3 is now the current major version, and Airflow 2 reached open-source end of life on 22 April 2026, so new deployments should plan on Airflow
• The limits are about operations.
• You run the servers, you apply the upgrades, you watch the scheduler and you fix the failures, which needs platform engineering capacity.

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Astronomer, sold as Astro, is the managed Airflow service for teams that want Airflow without running it. Developer deployments start at $0.35 an hour, Team deployments at $0.42 an hour on pay-as-you-go monthly billing, and workers cost from $0.13 an hour. The key detail is that workers scale to zero, so idle task compute is not billed, which keeps the cost down for pipelines that run in bursts.

• The platform adds observability, deployment management and support tiers, and it offers extended Airflow 2 support to April 2027 for teams that have n
• The migration effort from self-hosted Airflow is minimal, since the pipelines are the same DAGs.
• The limits are about billing and price transparency.
• Hourly billing is hard to predict, since the monthly total depends on how long deployments and workers run, and the higher tiers are quote only, so a

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Dagster is the best choice for data platform teams that think in assets rather than tasks. Pipelines are defined as Python assets with lineage and quality checks built in, so the catalogue shows where each dataset came from and whether it passed its checks. The open-source core is free under Apache 2.0, and Dagster+ Solo costs $10 a month plus $0.040 per credit, with Starter at $100 a month plus $0.035 per credit for up to three users, and serverless compute at $0.010 per minute.

• A credit is one asset materialisation or one operation, and neither plan includes credits, so the monthly total depends on how many assets you build.
• Pro is custom-quoted.
• The limits are about the vendor change and the billing.
• Prefect announced in July 2026 that it is acquiring Dagster Labs, and the combined company operates under the Prefect name from August 2026, so the tw

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Prefect is the best choice for Python teams that want flat seat pricing instead of per-run billing. Workflows are plain Python functions with decorators, which means a data engineer writes a function, adds a decorator and has a flow, with no DAG file to manage. The open-source core is free, the Hobby tier on Prefect Cloud is free for 2 users, Starter costs $100 a month for 3 users, Team costs $100 per user per month for 4 to 8 users, and Enterprise is custom-quoted on an annual contract.

• The plans are priced on users and workspaces, not on runs or tasks, so a team that runs many small flows pays the same as a team that runs few.
• The limits are about the seat price and the acquisition.
• The Team plan at $100 per user per month adds up fast for a large team, and Enterprise is custom and annual, so a big deployment needs a sales convers
• Prefect is also acquiring Dagster Labs, so the company now owns two orchestrators, and the long-term product plan is not yet fully clear.

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Kestra is the best choice for teams that want to define pipelines without writing Python. Flows are written in YAML, which means a data analyst or an operations engineer can build a pipeline without a Python environment, and the platform supports event-driven triggers, schedules and plug-ins for hundreds of systems. The open-source core is free under Apache 2.0, and the managed cloud is priced by quote, so a team that wants the hosted service must ask for a price.

• Kestra suits declarative pipelines, file-based workflows and teams that prefer configuration to code.
• The limits are the community size and the cloud price.
• Kestra has a smaller community than Airflow, Dagster or Prefect, so fewer integrations and fewer documented answers exist, and the managed cloud is qu
• The YAML model is also less flexible than Python for complex logic, since a flow that needs custom code must call out to a script.

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Mage is the best choice for teams that want a notebook interface for building pipelines. The open-source core is free, and the cloud plan starts at $29 a month plus compute, which covers the platform while the compute is metered separately. Pipelines are built in a notebook-style editor with blocks for data loading, transformation and export, which suits analysts who think in notebooks rather than DAG files.

• Mage supports dbt, Spark and common warehouses, and the interface shows the data at each step, which helps when a pipeline breaks.
• The limits are the compute charge and the ecosystem.
• The $29 a month covers the platform, but the compute is billed on top, so the real monthly total is higher, and the exact amount depends on how much t
• Mage also has a smaller ecosystem than Airflow, with fewer operators and fewer community answers.

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Orchestra is the best choice for lean data teams that run dbt and want a fast time to value. The Lean plan is free for 1 user, and Scale-Up costs $200 a month flat for up to 10 users, with no per-run meter. Pipelines are declared rather than coded, which means a small team can set up an orchestration layer in days rather than weeks, and the platform is built around dbt, so the lineage and the tests flow through without extra work.

• Orchestra suits teams that want orchestration without a framework to run, and the flat price makes the monthly cost easy to predict.
• The limits are the price jump and the scope.
• The free Lean plan covers only 1 user, so a team of two must pay $200 a month, which is costly for a small team, and the scope is narrower than Airflo
• If your team is dbt-first, lean and wants a flat price, Orchestra is the pick.

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