Best Data Orchestration Tools

Data orchestration tool reviews covering DAG authoring, retry and backfill handling, observability, local development and scaling behavior.

5 products

Astro
Astro

by Astronomer

No reviews yet

Astro is Astronomer's managed Apache Airflow service, a data orchestration platform for teams writing pipelines in Python, billed by usage per deployment hour.

Features

Has Pipelines defined as Python code
Has DAG graph view of task dependencies
Has Cron and interval schedules
Has Sensors and event-driven triggers
Has Per-task retries with backoff
Has Partitioned backfills
Has Asset-level lineage across pipelines
Has Local development environment with parity
Has Branch deployments per pull request
Has Git-driven deploys
Has Run failure alerts to Slack and PagerDuty
Has Task-level run history and logs
Has Dynamic task mapping at runtime
Has Hybrid execution on your own compute
Has Managed serverless workers
Has Freshness and asset checks
Has Open source orchestrator core
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Kestra
Kestra

by Kestra

No reviews yet

Kestra is an open-source orchestration platform for data, platform and software engineers, with workflows declared in YAML, self-hosted or in Kestra Cloud.

Features

Missing Pipelines defined as Python code
Has DAG graph view of task dependencies
Has Cron and interval schedules
Has Sensors and event-driven triggers
Has Per-task retries with backoff
Has Partitioned backfills
Has Asset-level lineage across pipelines
Has Local development environment with parity
Missing Branch deployments per pull request
Has Git-driven deploys
Has Run failure alerts to Slack and PagerDuty
Has Task-level run history and logs
Has Dynamic task mapping at runtime
Has Hybrid execution on your own compute
Has Managed serverless workers
Has Freshness and asset checks
Has Open source orchestrator core
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Mage
Mage

by Mage AI

No reviews yet

Mage is an open-source data pipeline and ETL tool with a managed cloud edition, Mage Pro, for data engineers who build, schedule and repair pipelines in code.

Features

Missing Pipelines defined as Python code
Missing DAG graph view of task dependencies
Has Cron and interval schedules
Has Sensors and event-driven triggers
Has Per-task retries with backoff
Has Partitioned backfills
Missing Asset-level lineage across pipelines
Has Local development environment with parity
Missing Branch deployments per pull request
Missing Git-driven deploys
Has Run failure alerts to Slack and PagerDuty
Has Task-level run history and logs
Has Dynamic task mapping at runtime
Has Hybrid execution on your own compute
Has Managed serverless workers
Has Freshness and asset checks
Has Open source orchestrator core
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Orchestra
Orchestra

by Orchestra

No reviews yet

Orchestra is a managed data orchestration platform for lean data teams, running dbt, Python and AI agent workflows as SaaS or on their own cloud.

Features

Missing Pipelines defined as Python code
Has DAG graph view of task dependencies
Has Cron and interval schedules
Has Sensors and event-driven triggers
Has Per-task retries with backoff
Has Partitioned backfills
Has Asset-level lineage across pipelines
Missing Local development environment with parity
Missing Branch deployments per pull request
Has Git-driven deploys
Has Run failure alerts to Slack and PagerDuty
Has Task-level run history and logs
Has Dynamic task mapping at runtime
Has Hybrid execution on your own compute
Has Managed serverless workers
Missing Freshness and asset checks
Missing Open source orchestrator core
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Prefect
Prefect

by Prefect

No reviews yet

Prefect is a workflow orchestration platform for Python data and ML engineers, with an Apache 2.0 open-source core and a hosted Prefect Cloud priced per seat.

Features

Has Pipelines defined as Python code
Missing DAG graph view of task dependencies
Has Cron and interval schedules
Has Sensors and event-driven triggers
Has Per-task retries with backoff
Missing Partitioned backfills
Has Asset-level lineage across pipelines
Has Local development environment with parity
Missing Branch deployments per pull request
Has Git-driven deploys
Has Run failure alerts to Slack and PagerDuty
Has Task-level run history and logs
Has Dynamic task mapping at runtime
Has Hybrid execution on your own compute
Has Managed serverless workers
Missing Freshness and asset checks
Has Open source orchestrator core
Visit Profile
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