Testing is one of the most critical activities in software development and using third-party APIs like DynamoDB in your code comes with challenges when writing tests. Today, I’ll show you how you can start writing tests for code that accesses DynamoDB from Python.
Counters can be used in all kinds of situations like gathering statistics about websites or billing systems. In this post we’ll dive deep into ways you can use DynamoDB to implement atomic and accurate counters using examples in Python.
You have probably seen architectures that use DynamoDB streams to perform change data capture on tables and Lambda functions to process those changes before. Today, we’ll do a deep dive into the underlying technology and explore how we can configure and tweak this configuration to our advantage.
Concurrent access to the same items in DynamoDB can lead to consistency problems. In this post I explain why that is and introduce optimistic locking as a technique to combat this issue.
DynamoDB supports complex data types like lists. In this post we take a look at different ways to interact with lists. We will use Python to write code that may be used in a data access layer to manipulate items with list attributes.
DynamoDB allows us to store complex data structures and deeply nested objects, but this complexity isn’t free. In this post we take a look at how different Lambda configurations impact the read times from boto3. We examine how different resource configurations can improve the read time of the same item by more than a factor of 12.
Data modelling in NoSQL databases is different from what we’re used to in the relational world. In this article we’ll talk about the process of data modelling in DynamoDB, single-table design and how to build a basic data access layer using python. We’ll explore these concepts by building a product catalog for a simple webshop that supports different query patterns and basic inventory management.
In this post I’ll introduce DynamoDB, a very powerful fully managed NoSQL wide-column data store in AWS. We will talk about data structures, the APIs to read and write data, indexes, as well as performance and cost considerations. In the end you will gain a solid understanding of the basics, which will serve as a starting point for further research.
