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Brief
Prefect

Prefect

Data Management Platformprefect.io

Prefect enables data teams to build, run, and monitor resilient data workflows with a Python-native framework that emphasizes developer experience, dynamic pipeline generation, and comprehensive observability.

Last updated May 11, 2026

Founded
2018
HQ
Washington, D.C., United States
Connections
5

At a glance

Employees
51-200
Funding
$47M
5integrations

About

Leading modern workflow orchestration platform competing with Apache Airflow and other data pipeline tools

Prefect is a workflow orchestration and dataflow automation platform, not an AdTech company. It provides infrastructure for data engineers and data scientists to build, schedule, and monitor data pipelines and workflows. The platform offers both an open-source Python framework (Prefect Core) and a managed cloud service (Prefect Cloud) that adds enterprise features like authentication, authorization, and enhanced observability. Prefect competes in the modern data orchestration space alongside tools like Apache Airflow, Dagster, and Temporal. Prefect is not part of the advertising technology ecosystem. Instead, it serves the broader data engineering and MLOps markets, helping organizations automate complex data workflows, ETL processes, machine learning pipelines, and other data-intensive operations. The company has positioned itself as a more developer-friendly and flexible alternative to traditional workflow orchestration tools, emphasizing ease of use, dynamic workflow generation, and native Python integration.

Business model

SaaS

Target market

Enterprise and Mid-Market

What they offer

  • Prefect Core

    Open-source Python workflow orchestration framework for building and running data pipelines

  • Prefect Cloud

    Managed cloud service providing orchestration, observability, and collaboration features for workflows

  • Prefect Server

    Self-hosted backend for workflow orchestration with UI and API

  • Prefect Automations

    Event-driven automation and alerting for workflow management

Key features

Python-native workflow definitionDynamic workflow generationReal-time observability and monitoringAutomatic retries and error handlingDistributed executionEvent-driven automationsParameterized workflowsCaching and incremental processing

Use cases

ETL and data pipeline orchestrationMachine learning workflow automationData warehouse managementBatch processing and scheduled jobsInfrastructure automationBusiness process automation

Customer segments

Data EngineersData ScientistsMLOps TeamsAnalytics TeamsDevOps Engineers

Tech & specs

Technology stack

PythonFastAPIPostgreSQLDockerKubernetesReact

Security & compliance

SOC 2 Type IIGDPR

Deployment

CloudOn-premiseHybrid

API

Yes

Corporate history
  • 2018Founded
See integrations with Prefect (5)

Explore further

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