Where's my lookup table? Modeling relational data in a denormalized world
Who is this presentation for?
- VPs of engineering, CIOs, CTOs, principal engineers, and software developers
When Amazon decided to migrate thousands of application services to NoSQL, many of those services required complex relational models that could not be reduced to simple key-value access patterns. The most commonly documented use cases for NoSQL are simplistic, and there’s a large amount of irrelevant and even outright false information published regarding design patterns and best practices for NoSQL applications. For this migration to succeed, Amazon needed to redefine how NoSQL is applied to modern online transactional processing (OLTP) apps.
NoSQL applications work best when access patterns are well defined, which means the sweet spot for a NoSQL database is OLTP applications. This is good because 90% of the apps that get written support a common business process which for all practical purposes is the definition of OLTP. One of the common steps in building an OLTP app is designing the entity relationship model (ERM) which essentially defines how the application uses and stores data. With a relational database management system- (RDBMS) backed application, the ERM was essentially mapped directly into the database schema by creating tables for the top-level entities and defining relationships between them as defined in the ERM. With NoSQL, the data is still relational, it just gets managed differently.
Rick Houlihan breaks down complex applications and effectively denormalizes the ERM based on workflows and access patterns. He demonstrates how to apply the design patterns and best practices defined by the Amazon team responsible for migrating thousands of RDBMS based applications to NoSQL and when it makes sense to use them.
- A basic understanding of RDBMS and some knowledge of SQL
- Familiarity with a normalized schema is a prerequisite
- General knowledge of NoSQL technology (useful but not required)
What you'll learn
- Understand that NoSQL databases still have to manage relational data and denormalization drives efficiency by tuning the data model to the access pattern
- Learn when using NoSQL makes sense and when it doesn't and how to start modeling relational data in a denormalized schema
Amazon Web Services
Rick Houlihan is a principal technologist and leads the NoSQL blackbelt team at AWS and has designed hundreds of NoSQL database schemas for some of the largest and most highly scaled applications in the world. Many of Rick’s designs are deployed at the foundation of core Amazon and AWS services such as CloudTrail, IAM, CloudWatch, EC2, Alexa, and a variety of retail internet and fulfillment-center services. Rick brings over 25 years of technology expertise and has authored nine patents across a diverse set of technologies including complex event processing, neural network analysis, microprocessor design, cloud virtualization, and NoSQL technologies. As an innovator in the NoSQL space, Rick has developed a repeatable process for building real-world applications that deliver highly efficient denormalized data models for workloads of any scale, and he regularly delivers highly rated sessions at re:Invent and other AWS conferences on this specific topic.
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