Prefect is a modern workflow orchestration framework designed to make building and monitoring data pipelines as simple as writing Python code. Positioned as a next-generation alternative to Apache Airflow, Prefect eliminates the need for DAG files, cron-based scheduling configurations, and rigid task dependency declarations. Instead, developers add decorators (@flow and @task) to existing Python functions, and Prefect automatically tracks execution, manages retries, handles concurrency, and provides observability – transforming ordinary scripts into observable, resilient workflows.

Prefect 2 (Orion), a complete rewrite released in 2022, introduced a dynamic, DAG-free execution model where workflows are defined imperatively rather than declaratively. This means tasks can be called conditionally, in loops, or based on runtime data, without pre-declaring a static dependency graph. The Prefect server provides a real-time dashboard for monitoring flow runs, viewing logs, inspecting task states, and managing deployments. Features include automatic retries with configurable policies, caching of task results, concurrent task execution (async-native), parameterized flows, notifications, and scheduling via cron, interval, or RRule expressions. Prefect integrates with cloud storage (S3, GCS, Azure Blob), databases, dbt, Spark, Kubernetes, Docker, and dozens of other tools through its collections (plugin) system.

Prefect is used by data engineering teams at companies including Progressive Insurance, Procter & Gamble, and numerous tech companies for ETL pipelines, ML training orchestration, and data quality monitoring. Prefect Cloud offers a managed orchestration service with team collaboration features, RBAC, audit logging, and automations (event-driven triggers).

Key Capabilities

  • Python-Native Decorators - Transform any Python function into an observed, retryable workflow task with a single @task or @flow decorator
  • Dynamic Workflows - Imperative, DAG-free execution model supporting conditionals, loops, and runtime-determined task graphs
  • Real-Time Dashboard - Web UI for monitoring flow runs, inspecting task states, viewing logs, and managing schedules in real time
  • Integrations Ecosystem - Collections (plugins) for dbt, Spark, AWS, GCP, Azure, Kubernetes, Docker, Snowflake, and many other tools

Cloud Equivalents

Prefect is the open-source alternative to AWS Step Functions, Google Cloud Composer, and Azure Data Factory for Python-centric data workflows. Unlike Airflow’s declarative DAGs, Prefect’s imperative model is more natural for data scientists and engineers writing Python. Prefect Cloud provides a managed option that eliminates server management.

Origins and History

Prefect was founded in 2018 by Jeremiah Lowin, who previously worked in quantitative finance and recognized the need for a more Pythonic workflow orchestration tool. Prefect 1.0 (Prefect Core) was released under the Apache License 2.0. Prefect 2.0 (codename Orion), a complete rewrite with the dynamic execution model, was released in July 2022. Prefect Technologies has raised over $60 million in venture funding. Prefect 3.0, released in 2024, further simplified the developer experience and improved performance.

Sources

  1. https://www.prefect.io/
  2. https://github.com/PrefectHQ/prefect