One core difference between Airflow and Prefect is simple: Airflow is a framework that forces your code to follow its rules, while Prefect is a library that adapts to your Python code. With Prefect, workflows can spin up and down dynamically - even using CPUs or GPUs. Even better, these decisions happen at runtime rather than being locked in a predefined graph. Your workflows adapt to real conditions, making better use of resources while keeping code clean and efficient. ⚙️ Dig into more reasons why modern teams choose Prefect over Airflow: https://prefec.tv/3FiHgcB
Prefect
Software Development
Washington, District of Columbia 26,346 followers
Trust your workflows, from script to scale.
About us
Modern workflow orchestration for data and ML engineers
- Website
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http://www.prefect.io
External link for Prefect
- Industry
- Software Development
- Company size
- 51-200 employees
- Headquarters
- Washington, District of Columbia
- Type
- Privately Held
Products
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Prefect
Data Science & Machine Learning Platforms
Prefect is open-source workflow orchestration for building, observing, and reacting to your data pipelines. With Prefect, control and observe: 1. What code runs, and the data it handles 2. When it runs, scheduled or triggered by an event 3. Where it runs, and the systems it talks to
Locations
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Primary
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1200 18th St NW
Washington, District of Columbia 20036, US
Employees at Prefect
Updates
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Step back and see the complete picture, not just individual workflows - with Lenses in Prefect. Lenses are our new approach to visualizing and comprehending your workflow ecosystem beyond the data ✨ Through shared resources, patterns and relationships emerge when these workflows interact that span beyond data lineage. Lenses in Prefect transform how we visualize and understand complex data platforms.
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Grab some peanuts and Cracker Jack for the second installment of our Moneyball Marvin series, as we build on our baseball data analysis foundation by creating an automated data pipeline to process new game data. This tutorial covers the complete process of setting up event-driven data workflows and creating a dashboard for baseball statistics. https://prefec.tv/3FobB9l
Building an Event-Driven Baseball Data Pipeline with Prefect, dbt, Snowflake & Hex
https://www.youtube.com/
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We've got a new NYC home base! 🗽✨ Super excited to share that Prefect now has a landing spot in New York City! We just had our office warming party this week and it was awesome to see so many faces in our new space. Looking forward to all the creativity and community that'll happen here! #PrefectCommunity
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Thanks for the love Ben 🫶 This guide is incredible, we're honored to have it in our library to help even more teams! #PrefectCommunity #DataOrchestration
There are only a small handful of tools in the data processing ecosystem that I love. Prefect and Modal happen to be 2 of them, and they work incredibly well together. I recently wrote a full guide to deploy scalable workflows on prefect that are scheduled and executed on modal, and the prefect team added it to their official documentation. If you're looking to level up your teams data processing with best-in-class tooling, give it a read: https://lnkd.in/eqSHkJ4p
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Excited to share our latest Prefect OSS release: "Entomologists HATE This One Weird Trick" 🪲 Check out the full release notes and...bug fixes. https://lnkd.in/gWtQce4V What creative naming conventions does your team use? Drop a favorite software release name in the comments! #Prefect #OpenSource #Python #DataOrchestration #DevTools
Naming things is hard, and the hardest part of every week is working with the Prefect OSS team to come up with fun release titles. Today we released "Entomologists HATE This One Weird Trick" which I think is a strong contender for a new favorite name. Other recent hits have been: • Cache Rules Everything Around Me • The Numbers Are Made Up But The Features Are Real • Several Types of Small Code Fixes Gathered Together in a Release and Grooving with a K8s Pod Check out our latest release here: https://lnkd.in/gqAds3Zp and peruse our catalogue 😂 Do you have creative naming conventions on your team or have a favorite software release title?
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What are you doing tomorrow? 👀 It’s not too late to join us for Observing Airflow DAGs in Prefect at 11 am PT. You'll learn how to monitor Airflow DAGs in Prefect with specific code you can copy-paste into your setup. Secure your spot now to take the first step toward achieving your data engineering goals more effectively! https://prefec.tv/4buMu0U
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We're incredibly proud to see how LiveEO is revolutionizing geospatial analytics! 🛰️ Their impressive results speak volumes, 63% reduction in AWS costs with smarter scaling?! 😮💨 Nice work. We're honored to be part of your journey in delivering faster, more precise geospatial intelligence to your customers. 💪 #DataOrchestration #GeospatialAnalytics #PrefectCommunity
Ever wondered what it takes to transform petabytes of satellite data into actionable insights? Orchestrating petabytes of geospatial data for infrastructure monitoring is no small feat. By optimizing our workflows, we’ve significantly improved scalability, efficiency, and cost-effectiveness. Prefect’s Python-first orchestration framework played a key role in streamlining deployments and ensuring robust validation before provisioning thousands of compute instances. The impact? ✔️ Accelerated deployment of AI-driven insights ✔️ 63% reduction in AWS costs with smarter scaling ✔️ Increased development velocity for new analytics This transformation allows us to deliver even more value to our customers by providing faster, more precise geospatial intelligence. Learn more about how we were able to achieve this in a case study on Prefect's website 👇 https://hubs.li/Q038YmNX0
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At Prefect we're increasingly using uv. It helps you reduce the pain of Python virtual environment management, slow package installs, and unreproducible environments. We've written up our learnings: Take a read about What Data Professionals Need to Know about uv – so you can start saving time and money ⌛💰 Have you used uv yet? https://prefec.tv/4h4xl7t
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We’re sending you off into the weekend with one of our most requested tutorials yet–Migrating from Airflow ➡️ Prefect. This guide walks you through a step-by-step migration, helping you transition from Airflow DAGs to Prefect flows while mapping key concepts, adapting infrastructure, and optimizing deployments. By the end, you’ll have a streamlined, scalable orchestration system that lets your team focus on engineering. https://prefec.tv/3Dagx12