Exploring Amazon DynamoDB: Insights from the AWS Database Blog

Empirical Testing and Query Measurement in Amazon DynamoDB

Exploring Amazon DynamoDB: Insights from the AWS Database BlogMore Info

In this article, we delve into how our team efficiently conducted empirical analysis of Amazon DynamoDB queries. Our objective was to take an existing DynamoDB database, creatively transform the data, and then store it in a new DynamoDB setup. After eight months of diligent work on our initiative, we were pleased to share our findings.

Enhancing Scan Latency in Amazon DynamoDB Through Schema Design

By Sarah Lee, Mark Thompson, and Alice Green
Published on June 12, 2019

This blog post illustrates how the structure of Amazon DynamoDB tables impacts scan performance. We provide strategies for optimizing table scan durations. As a NoSQL database with a flexible schema, DynamoDB allows items within the same table to have varying attributes.

SimilarWeb’s Transition from Couchbase to Amazon DynamoDB and a 70% Cost Reduction

By Oliver Smith, Emily Brown, and Rachel Taylor
Published on May 14, 2019

In this guest post, Oliver Smith, a software engineer at SimilarWeb, collaborates with AWS solutions architect Emily Brown and senior technical account manager Rachel Taylor. NoSQL databases cater well to numerous modern applications across mobile, web, and gaming platforms, requiring scalable, adaptable, and highly functional database solutions. For further insights, check out this additional blog post.

Ad Tech Use Cases and Design Patterns in Amazon DynamoDB

By James Carter
Published on April 8, 2019

Advertising technology companies leverage Amazon DynamoDB to store various marketing data types, including user profiles, events, clicks, and more. This piece outlines the prevalent use cases and design patterns observed in the ad tech industry.

Gaming Use Cases and Design Patterns in Amazon DynamoDB

By James Carter
Published on April 2, 2019

Gaming companies utilize Amazon DynamoDB across various facets of game platforms, such as game state, player data, session history, and leaderboards. The key advantages include its capacity to reliably scale to millions of concurrent users while maintaining low latency, often in the single-digit milliseconds range.

Understanding Amazon DynamoDB Encryption with AWS Key Management Service

By Kate Gomez and Tom Harris
Published on April 1, 2019

As applications grow in scalability, customers are increasingly adopting flexible data structures and database engines. The popularity of NoSQL data stores is rising, attributed to their adaptable data models for modern application development.

Tuning AWS Java SDK HTTP Request Settings for Amazon DynamoDB Applications

By Sam Parker and Lisa White
Published on March 28, 2019

This post has been updated for accuracy, offering additional guidance on balancing high and low timeout settings. Amazon DynamoDB is engineered to deliver low-latency and high-throughput performance, ideal for applications at scale.

Designing Global Secondary Indexes in Amazon DynamoDB

By Greg Adams
Published on March 14, 2019

During my college years, I used entity-relationship diagrams to model system requirements for relational databases. This methodology encompassed identifying system entities and defining their interrelationships before structuring them into database tables, ensuring the necessary queries were supported.

A Comprehensive Guide to the Amazon DynamoDB Console

By Emily Roberts
Published on March 7, 2019

Since its launch in 2012, Amazon DynamoDB has evolved into a fully managed, multi-region, multimaster database service, renowned for delivering fast and predictable performance at any scale. It offers multiple options for executing operations, including a web-based console, the AWS Command Line Interface (CLI), and various SDKs.

Design Patterns for High-Volume Time-Series Data in Amazon DynamoDB

By Alex Casalboni
Published on February 25, 2019

Time-series data represents changes over time, making it crucial for various applications.

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