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Astronomer Blog

Culture / Data Science / Dev / Growth

Greg Neiheisel

Recent Posts by Greg Neiheisel:

Building Next-Generation Data Infrastructure with Apache Mesos and DC/OS

 Photo cred: CarrieLu / Flickr

Estimated reading time: 8 minutes and 52 seconds

Astronomer is a data engineering platform that collects, processes and unifies users' enterprise data, so they can get straight to analytics, data science and—more importantly—insights. We make it easy to capture data from any source and send it to any location, from a custom dashboard for visualization to a database for analysis.

Data is becoming the most valuable resource a company owns, and building pipelines that can accommodate all of a company's use-cases while easily scaling is a challenging problem. We’re lowering the barrier to entry for anyone who wants to put their data to work.

Topics: dev

Our Open Source Philosophy

Estimated reading time: 3 minutes, 10 seconds

Last year, I wrote a blog post about why we built our platform on AWS and rebuilt it with open source. It chronicles our journey to build our ideal unified system, one that checks all our boxes (like cross-infrastructure, secure, efficient, highly available, self-healing and able to execute long running processes as well as spin up one-off processes and specialized clusters of machines on the side). 

But this post is different.

Topics: culture dev

Airflow at Astronomer

Estimated reading time: 8 minutes, 47 seconds

At Astronomer, we're creating a modern platform for organizations to build data pipelines to power their analytical and machine learning workloads. Our goal is to make it extremely simple for anyone to set up a data pipeline without having to worry about everything involved with keeping that pipeline running. We pride ourselves on being adaptable enough to extract data from anywhere and get it into your data lake or data warehouse.

Topics: dev

Why We Built Our Data Platform on AWS, and Why We Rebuilt It with Open Source

Astronomer is a modern platform built to outfit organizations with a solid data infrastructure to support machine learning and analytical workloads. In other words, we help you organize, centralize and clean your data through a personalized data engineering experience. We exist because we believe the internet age is just a precursor to something much larger, something with the potential to push the world forward in the same ways the Agricultural and Industrial Revolutions did: the Data Revolution.

Topics: big data startups dev