What, Where, and How of Polyglot Persistence

As we started embracing Big Data and NoSQL across a number of projects, it quickly became clear that one technology is not going to be a solution for all of our needs. In this talk we share our experiences with polyglot persistence. We begin by outlining the issues relational technology has with scalability and new data formats. We then illustrate the examples of dominant NoSQL technologies and how they fit into the big picture. We explore the polyglot persistence in the cloud and its relationship with microservices.

You will benefit from getting a clear picture of what type of NoSQL data store is a good match for different data processing pieces of puzzle and how to make an optimal choice when selecting pragmatic polyglot solutions.

What is polyglot persistence?
The relational database problems
Taming big data with Hadoop and Map Reduce
Scalability with Key/Value and Columnar stores
Flexibility of Document stores
Finding connections with Graph databases
Combining different stores in a system
Cloud and polyglot persistence
The impact of microservices
NoSQL integration strategies

Dr. Vladimir Bacvanski has over two decades of engineering experience with mission critical and distributed enterprise systems and data technologies. Vladimir has helped a number of companies including the US Treasury, the Federal Reserve Bank, the US Navy, IBM, Dell, Hewlett Packard, JP Morgan Chase, General Electric, BAE Systems, AMD, and others to select, transition to, and apply new software and data technologies.

Vladimir is published worldwide and is a keynote speaker, session chair, and workshop organizer at leading industry events. As a founder of SciSpike, Vladimir is focusing on Big Data technologies and highly scalable reactive software architectures with node.js and Scala. Vladimir is the author of the O'Reilly course on Big Data and NoSQL.