Hadoop and MySQL: Friends with Benefits

MySQL offers compelling benefits to developers in the form of speed, reliability, data integrity and scalability. While MySQL has been proven to handle petabytes of data, sometimes a relational database just doesn’t fits the intended task. For instance, applications that require massive parallel data processing or logging on the backend to create a final data set, may find it beneficial to outsource some of the tasks to a massive parallel processing system, such as Hadoop.

Hadoop is a cross-platform framework written in Java that’s designed to support data intensive distributed applications with a focus on data processing. Google’s MapReduce and Google File System papers inspired Hadoop’s creation. Hadoop’s computational paradigm, named map/reduce, divides an application into several small fragments allowing tasks to be executed on any node in the cluster.

MySQL and Hadoop working in tandem can provide a path to innovation. The best of both worlds can be achieved by taking this innovative approach.

In this presentation, we take a look at case studies and use cases where Hadoop and MySQL together are providing answers to some very complex challenges for innovative startups.