Amazon DynamoDB references

Amazon DynamoDB is one of my favourite databases.

It’s a pain during the early stages of a project because you have to design your data model based on your queries, which is a good exercise to do anyway. If you are working on a new project without clear query patterns it can be hard to come up with an efficient data model upfront.

My favourite feature of DynamoDB is its predictability and constant performance. I know what to expect from it, and I can plan around it. Constraints are good for performance and reliability.

This article lists resources diving into how DynamoDB works under the hood.

AWS docs

Publications

Abstract: NoSQL cloud database services, like Amazon DynamoDB, are popular for their simple key-value operations, unbounded scalability and predictable low-latency. Atomic transactions, while popular in relational databases, carry the specter of complexity and low performance, especially when used for workloads with high contention. Transactions often have been viewed as inherently incompatible with NoSQL stores, and the few commercial services that combine both come with limitations. This talk examines the tension between transactions and non-relational databases, and it recounts my journey of adding transactions to DynamoDB. I conclude that atomic transactions with full ACID properties can be supported without unduly compromising on performance, availability, self-management, or scalability.

Abstract: Amazon DynamoDB is a NoSQL cloud database service that provides consistent performance at any scale. Hundreds of thousands of customers rely on DynamoDB for its fundamental properties: consistent performance, availability, durability, and a fully managed serverless experience. In 2021, during the 66 hour Amazon Prime Day shopping event, Amazon systems including Alexa, the Amazon.com sites, and Amazon fulfillment centers, made trillions of API calls to DynamoDB, peaking at 89.2 million requests per second, while experiencing high availability with single-digit millisecond performance. Since its launch in 2012, DynamoDB’s design and implementation have evolved in response to our experiences operating it. The system has successfully dealt with issues related to fairness, traffic imbalance across partitions, monitoring, and automated system operations without impacting availability or performance. Reliability is essential, as even the slightest disruption can significantly impact customers. This paper presents our experience operating DynamoDB at a massive scale and how the architecture continues to evolve to meet the ever-increasing demands of customer workloads.

Abstract: NoSQL cloud database services are popular for their simple key-value operations, high availability, high scalability, and predictable performance. These characteristics are generally considered to be at odds with support for transactions that permit atomic and serializable updates to partitioned data. This paper explains how transactions were added to Amazon DynamoDB using a timestamp ordering protocol while exploiting the semantics of a key-value store to achieve low latency for both transactional and non-transactional operations. The results of experiments against a production implementation demonstrate that distributed transactions with full ACID properties can be supported without compromising on performance, availability, or scale.

Videos and talks

Search the AWS Events channel: https://www.youtube.com/@AWSEventsChannel/search?query=dynamodb

Other


August 19, 2025