DataStax Enterprise, powered by Apache Cassandra, lets people solve challenges, avoid risks, and transform how they interact with their customers. But that’s after they figure out the data model for this new kind of database. Get the data model right, and you’re on your way. Get it wrong, and you’ll waste development cycles trying to solve problems that you could have avoided. It’s query-based data modeling, and it’s very different from relational modeling, so take some time now to learn how to do it correctly.
We’ve got an array of data modeling resources to get you started.
Data Modeling Webinars
Relational systems have always been built on the premise of modeling relationships. As you will see, static schema, one-to-one, many-to-many still have a place in Cassandra. From the familiar, we’ll go into the specific differences in Cassandra and tricks to make your application fast and resilient.
Sure you can do some time series modeling. Maybe some user profiles. What’s going to make you a super modeler? Let’s take a look at some great techniques taken from real world applications where we exploit the Cassandra big table model to it’s fullest advantage.
You know you need Cassandra for its uptime and scaling, but what about that data model? Let’s bridge that gap and get you building your game changing app. The goal of this talk is to get you comfortable working with data in Cassandra throughout the application lifecycle.
Functional data models are great, but how can you squeeze out more performance and make them awesome? Let’s talk through some example Cassandra 2.0 models, go through the tuning steps and understand the tradeoffs. Many time’s just a simple understanding of the underlying Cassandra 2.0 internals can make all the difference. I’ve helped some of the biggest companies in the world do this and I can help you. Do you feel the need for Cassandra 2.0 speed?
Using concrete, real-world examples, this webinar will show how abandoning modeling altogether is a recipe for disaster, how experienced relational modelers can leverage their skills for NoSQL projects, how the NoSQL context both simplifies and complicates the modeling endeavor, and how lessons learned modeling for NoSQL projects can make you a more effective modeler for any kind of project.