DynamoDB case studies
DynamoDB is currently used by more than a million customers globally (9). These range from small applications performing a few requests here and there, to enterprise-grade systems that continually require millions of requests per day, and all these and more depend on DynamoDB to power mission-critical services.
There is an incredibly high chance that you have indirectly been a DynamoDB user if you have spent any time on the internet. From retail to media to motorsports and hospitality, DynamoDB powers a sizable number of online applications. One of the best ways to find out about the incredible workloads and systems that not only DynamoDB but also AWS helps to power is to hear it through the voice of their customers.
What’s key to think about overall is that while these case studies shine a light on some of the large-scale DynamoDB solutions in use today, they may not completely represent what you or I want or need to use DynamoDB for right now. Importantly, the takeaway here is that you and I and every developer, start-up, or enterprise have the same power at our fingertips with DynamoDB as the following case studies. Every feature these customers have access to within the service, you do too, and that’s where the power of not only DynamoDB but also AWS comes in.
The upcoming case studies illustrate how DynamoDB users adopted the service either to overcome specific challenges or to leverage their trust in the platform based on prior positive experiences with the technology.
Amazon retail
As we briefly covered in the previous section, Amazon.com, the retail platform, heavily relied on its existing relational databases but was struggling to scale its system to keep pace with the rapid growth and demand of the platform. The Amazon Herd team decided to move over to DynamoDB (10).
Migrating from a relational database to a NoSQL offering takes time, planning, and understanding of the workload that is going to be migrated. The internal teams (as we’ve highlighted) were able to identify that ~70% of the current database queries were that of the key-value type (the lookup was performed by a single primary key with which a single row was returned), which aligns well with NoSQL.
Once fully implemented, one of the many benefits the Herd team was able to make use of was being able to reduce their planning and the time required to scale the system for large events by 90%. This allowed the team to spend more time in other areas, such as creating new value-adding features for the Amazon retail platform.
On the back of this success, DynamoDB powers many of the mission-critical systems used within Amazon (including multiple high-traffic Amazon properties and systems). To further exhibit just how powerful and instrumental the move to DynamoDB was, and over the period of the multiple-day Amazon Prime Day event in 2023, in an official post by AWS (11), the following is stated:
Let’s just think about that for a second – 126 million requests per second?! For any service to be able to deliver this level of throughput is an incredible feat. What’s more, this was delivered on top of all other AWS customers’ workloads across the globe, without breaking a sweat. Whatever you can throw at DynamoDB, the service can handle it in its stride. To this day (and every year when I read the latest Amazon Prime Day stats), I’m in awe of the tremendous power that DynamoDB offers. This is one of the many reasons why so many customers choose DynamoDB to power their workloads.
What is Amazon Herd?
Amazon Herd is an internal orchestration system that helps to enable over 1,300 workflows within the Amazon retail system. Herd is used to manage services ranging from order processing and certain fulfillment center activities as well as powering parts that help Amazon Alexa to function in the cloud.
Disney+
In April 2021, the Walt Disney Company outlined in a press release (12) how they are using AWS to support their global expansion of Disney+, one of the largest online streaming video services in the world. Disney+ scales part of its feature set globally on DynamoDB.
If, like me, you have used Disney+ and have added a video to your watchlist, or perhaps you have started watching any of their video content, paused it, and have come back later, or even watched the rest of it on a different device, these features have data that persisted under the hood with DynamoDB. Globally, these events (and more) amount to billions of customer actions each day.
Disney+ takes advantage of AWS’ global footprint to deploy its services in multiple regions (13), and with DynamoDB, they are making use of a feature called Global Tables (14) (see Chapter 13, Global Tables). In a nutshell, Global Tables provides a fully-managed solution for multi-region, multi-active tables within DynamoDB. You simply enable the feature and decide which regions you want to be “active” in, and DynamoDB takes care of regional provisioning, any data back-filling, and then all ongoing replication for you. It’s incredibly powerful and requires no maintenance from you. It’s just one of the mechanisms in place that we can refer to when thinking about DynamoDB’s “click-button” scaling.
With Global Tables in place, many of the Disney+ APIs are configured to read and write content within the same region where the data is located, reducing overall latencies to and from the database. Global Tables also allows their services to failover geographically from one entire region to another, from both a technical failure perspective as well as being able to perform maintenance in a given region without incurring user downtime or affecting the availability and usability of the overall Disney+ service.
I highly recommend watching an AWS re:Invent video titled How Disney+ scales globally on Amazon DynamoDB (15). Next, let us review the characteristics of workloads that may not be suited for DynamoDB.
