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Barstool Sports
Barstool Sports
Case study: Barstool Sports

In 15 minutes, Barstool Sports saved millions in outage avoidance

Barstool Sports has quickly become one of the world’s largest podcast platforms, serving millions of users. From day one, Barstool built their massive media platform on a cloud-native stack. As they grew, and their platform required more connections, they ran into major issues with Amazon’s Aurora MySQL database. They originally set up PlanetScale as a fail-over, but during a major outage, they made the switch permanent and haven’t looked back.

Without DevOps experts, Barstool needed a more powerful database.

In 2017 Andrew Barba was hired as an iOS engineer for Barstool. When he found himself in charge of the engineering team, he knew he wanted to choose an attractive stack for engineers. He knew Node.js and AWS would be the backbone, but didn’t want to burden his team with having to be DevOps experts. The team quickly built a pretty great serverless stack leveraging Lambda, REST APIs, and iOS Native apps, and wanted a database that would play nice with Lambda. Amazon’s Aurora database (cloud-hosted MySQL) seemed to be a logical fit.

The problem they noticed is a common one with serverless architectures. Andrew explains this as a mismatch of velocity. While their Lambda processes could scale incredibly fast, adding thousands of containers per second, their attempts to add read replicas to support new Lambda clients were extremely slow and expensive. “We’d just start adding read replicas, but this would take 3-4 minutes. This is the difference from scaling front-end to back-end. Most databases, including Aurora, just aren’t able to handle the demands of a serverless product. You are limited by how powerful your database is.”

In the end, we saved 20-30% by switching to PlanetScale.

It was pretty obvious that if PlanetScale could handle our traffic that we would be in much better shape. It did things like query collapsing and connection pools which we were very excited about, and most importantly didn’t require us to implement the orchestration layer.


Had to be able to handle peak loads of thousands of connections


Needed to auto-scale so that the team didn’t have to manage spinning up new replicas


Had to handle millions of transactions a second

Powerful logging

Predictable pricing

Ideally cheaper than Aurora :)


Handle migrations without scaling up a database 4x, and query statistics

While Andrew was exploring his options, he knew that Vitess was capable of solving many of his problems. However, he didn’t want all of his engineers to have to learn a new and super-complex tool. That’s when he discovered PlanetScale.

Results: Saved money and saved time

The team at Barstool signed up quickly after finding PlanetScale, and in September of 2021, created a trial database, and started syncing data from their main Aurora database to their PlanetScale database. At the time this was a fairly manual process, but it’s now much easier with PlanetScale's import feature. Because Barstool had so many outages, they decided to run data through PlanetScale concurrently alongside Aurora to be able to monitor how it handled their traffic. As Andrew describes it, the Aurora outages were incredibly costly, with their worst, a 45-minute outage quickly losing them a couple of million dollars. During one of their events, and during the PlanetScale trial, a query started misfiring and they had another complete Aurora outage. As Andrew describes it — that was the moment they switched to PlanetScale.

Because PlanetScale is running MySQL, Barstool was able to switch very quickly by merging a single branch of code that only contained a new connection string and a few driver changes.

MySQL went down completely. A query wasn’t executing. We could see that the PlanetScale database was handling it fine on a newer version of MySQL. We literally cut over in 15 minutes. We did a big post-mortem and five months later we haven’t looked back. PlanetScale is incredibly powerful and we just let it do its thing.

What the team at Barstool had not anticipated was seeing their bill go down after switching over to PlanetScale. “Honestly we did not anticipate the savings from a time or money perspective,” said Andrew “There were unplanned costs, like migrations, when managing our own database. We would have to scale up our resources to 4× to do a single migration. PlanetScale just handles migrations with a click of a button. In the end, we saved 20-30% by switching to PlanetScale.” Since PlanetScale prices its cloud database on usage instead of resources, scaling up and down has no effect on cost. Instead, the database automatically adjusts resources, behind the scenes, as needed for the usage.

In the end, we saved 20-30% by switching to PlanetScale.

In the end, Barstool says the added benefits of working with PlanetScale just keep coming. When asked, Andrew said the team at PlanetScale has made his team’s task much simpler.

We used to check the AWS dashboard practically nightly. Honestly, we never think about PlanetScale. That’s the way it should be. The reality is that our team is called the product team — we build products. We don’t want to be DevOps experts, and frankly we don’t need DevOps database work. We want to always focus on making our product better.

Barstool Sports
Previous Database
Amazon Aurora Serverless
Achieved with PlanetScale
Power and Velocity

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