Data Orchestration Tools

Mage vs Prefect

Compare Mage and Prefect side-by-side. See feature differences and pricing in the Data Orchestration Tools category.

by Mage AI

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Pricing: Mage OSS free and self-hosted; Starter $29/mo and Team $100/mo billed monthly, each plus $0.012 per execution minute; Enterprise by quote; 7-day trial

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.

12 /17 features Full profile

Prefect

by Prefect

No reviews yet

Pricing: Hobby tier free; Starter $100 a month flat; Team $100 per user a month for 4 to 8 users; both billed monthly. Enterprise by quote, billed annually. No trial on paid plans.

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.

13 /17 features Full profile

Feature Comparison

Data Orchestration Tools features side-by-side

Feature	Mage 12/17 features	Prefect 13/17 features
Pipelines defined as Python code Workflows and their dependencies are declared in Python files kept in version control.	No	Yes
DAG graph view of task dependencies A visual graph shows each pipeline's tasks, dependencies and current run state.	No	No
Cron and interval schedules Pipelines run on cron expressions or fixed intervals with timezone handling.	Yes	Yes
Sensors and event-driven triggers A run starts when a file lands, an upstream asset updates or an external event arrives.	Yes	Yes
Per-task retries with backoff Each task declares its own retry count and delay before the run is marked failed.	Yes	Yes
Partitioned backfills Re-run a pipeline over a range of past dates or partitions from the UI or CLI.	Yes	No
Asset-level lineage across pipelines Tables and files produced by tasks are tracked as assets with upstream and downstream links.	No	Yes
Local development environment with parity Run the orchestrator locally with the same code that ships to production.	Yes	Yes
Branch deployments per pull request Each open pull request gets its own deployment for testing before merge.	No	No
Git-driven deploys Merging to a branch deploys pipeline code to the environment automatically.	No	Yes
Run failure alerts to Slack and PagerDuty Failed or late runs notify chat and on-call tools with a link to the run.	Yes	Yes
Task-level run history and logs Every task attempt keeps its logs, duration and status for later inspection.	Yes	Yes
Dynamic task mapping at runtime A task fans out into many parallel instances based on data discovered during the run.	Yes	Yes
Hybrid execution on your own compute Tasks execute on workers in your own cloud or Kubernetes while the vendor hosts the control plane.	Yes	Yes
Managed serverless workers The vendor supplies compute for runs so no worker infrastructure is operated.	Yes	Yes
Freshness and asset checks Declare expected update times and checks on produced assets and surface breaches in the UI.	Yes	No
Open source orchestrator core The scheduler and executor are open source and can be self-hosted without a subscription.	Yes	Yes
Overall Rating	No reviews yet	No reviews yet

Mage 12/17 features

Pipelines defined as Python code: No
DAG graph view of task dependencies: No
Cron and interval schedules: Yes
Sensors and event-driven triggers: Yes
Per-task retries with backoff: Yes
Partitioned backfills: Yes
Asset-level lineage across pipelines: No
Local development environment with parity: Yes
Branch deployments per pull request: No
Git-driven deploys: No
Run failure alerts to Slack and PagerDuty: Yes
Task-level run history and logs: Yes
Dynamic task mapping at runtime: Yes
Hybrid execution on your own compute: Yes
Managed serverless workers: Yes
Freshness and asset checks: Yes
Open source orchestrator core: Yes

No reviews yet

Prefect 13/17 features

Pipelines defined as Python code: Yes
DAG graph view of task dependencies: No
Cron and interval schedules: Yes
Sensors and event-driven triggers: Yes
Per-task retries with backoff: Yes
Partitioned backfills: No
Asset-level lineage across pipelines: Yes
Local development environment with parity: Yes
Branch deployments per pull request: No
Git-driven deploys: Yes
Run failure alerts to Slack and PagerDuty: Yes
Task-level run history and logs: Yes
Dynamic task mapping at runtime: Yes
Hybrid execution on your own compute: Yes
Managed serverless workers: Yes
Freshness and asset checks: No
Open source orchestrator core: Yes

No reviews yet

Pricing

Mage

Mage OSS free and self-hosted; Starter $29/mo and Team $100/mo billed monthly, each plus $0.012 per execution minute; Enterprise by quote; 7-day trial

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Prefect

Hobby tier free; Starter $100 a month flat; Team $100 per user a month for 4 to 8 users; both billed monthly. Enterprise by quote, billed annually. No trial on paid plans.

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