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Prefect

Freemium

Workflow orchestration platform enabling users to write data, ML, and agent workflows as plain Python functions with built-in scheduling, retries, caching, and recovery capabilities.

Launched 2018-10-01

About Prefect

Prefect is a modern Python-native orchestration engine for data pipelines. Strong defaults, friendly UI, and a generous free tier. Prefect stands out for python-based workflow definition with decorators, durable execution with automatic retries and recovery, scheduling including cron, event-driven, and backfills, and observability and monitoring across all runs and teams. Teams pick it because python-native and great developer experience. Things to keep in mind: less mature than airflow for very large deployments.

Prefect is a freemium tool and launched on 2018-10-01. It sits in the Coding and Automation space and is best used to Data pipeline orchestration with automatic healing and recovery, Machine learning workflow scheduling and monitoring, Agent-based automation and task execution.

Pricing

Pricing model
Subscription
Currency
USD
Payment options
Monthly / Annual
HobbyFree
  • 2 Users
  • 1 Workspace
  • 5 Deployments
  • 500 mins/mo Serverless Credits
  • Webhooks
  • Service Accounts
  • 5 Automations
  • 7 days Run Retention
StarterCustom
TeamCustom
ProCustom
EnterpriseCustom
  • Priority support with 30-minute response SLA
  • SSO
  • SCIM
  • Audit Log Retention
  • Object-level RBAC
  • IP Allowlisting
  • PrivateLink
  • Sandbox Environment

Features

  • Python-based workflow definition with decorators
    It's a defining strength of Prefect — especially when teams need to data pipeline orchestration with automatic healing and recovery.
  • Durable execution with automatic retries and recovery
    Comes up again and again in user reviews of Prefect for data pipeline orchestration with automatic healing and recovery.
  • Scheduling including cron, event-driven, and backfills
    Why Prefect is a go-to choice for data pipeline orchestration with automatic healing and recovery.
  • Observability and monitoring across all runs and teams
    Cited as a top reason teams pick Prefect over competitors when they need to data pipeline orchestration with automatic healing and recovery.
  • Multi-infrastructure deployment (Kubernetes, ECS, VPC, serverless)
    Pairs naturally with the rest of the Prefect workflow for data pipeline orchestration with automatic healing and recovery.
  • Serverless managed compute option
    Built-in support for serverless managed compute option — used for data pipeline orchestration with automatic healing and recovery.
  • Automations and alerts for failures and SLA violations
    It's a defining strength of Prefect — especially when teams need to data pipeline orchestration with automatic healing and recovery.
  • Work pools and custom execution environments
    Comes up again and again in user reviews of Prefect for data pipeline orchestration with automatic healing and recovery.

Pros

  • Python-native
  • Great developer experience
  • Generous free tier

Cons

  • Less mature than Airflow for very large deployments
  • Some integrations missing
  • Pricing jumps at scale

AI Models used

The foundation models that power Prefect under the hood.

OpenAI GPT-4OpenAI

Powers AI-assisted workflow generation and natural language understanding features within the Prefect platform.

Categories

Coding
Automation
Workflow Orchestration
Data Engineering
Machine Learning
DevOps

Best use cases

Data pipeline orchestration with automatic healing and recovery
Machine learning workflow scheduling and monitoring
Agent-based automation and task execution
ETL/ELT operations replacing brittle cron jobs
Multi-team workflow visibility and observability
Production data operations at scale

Frequently Asked Questions

General

Related & Connected

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