The number of options for storing, manipulating and accessing data have exploded over the last decade. Open source “NoSQL” (not-only SQL) have spread like wildfire among organizations with cutting-edge analytics. They, along with Hadoop, have lowered the cost barrier to powerful, flexible and incredibly scalable implementations of systems that access unstructured, semi-structured and flexibly-structured data in addition to relational data. However, the learning- and investment-curves have been prohibitive for many organizations. It is all too common that a company would like to advance its database and analytics capabilities with non-relational data but they don’t have the time, human resources or budgets to dedicate to spinning-up and learning how to use these new technologies.
The answer to this challenge is not that all organizations must become cutting-edge with their database technologies. There are good reasons for many, if not most, organizations to take a more conservative approach, which must involve seeing how far their existing technologies can take them. This has created a strong incentive for the big relational DBMS vendors to enhance their products to allow them to handle much of what is being done with these newer database systems, and those vendors are starting deliver on that need in a big way.
What led to this expansion of relational databases into the realm of non-relational data? Should your organization invest in implementing those NoSQL database systems or should your strategy be to align with your relational DMS vendor’s ongoing enhancements to meet those needs? Join TDWI faculty instructor Aaron Fuller and Geoge Baklarz from IBM for a discussion about these critical questions and a demonstration of how one of the leading RDBMS vendors is enhancing their product to meet their customers’ NoSQL needs.
You Will Learn:
Individual, Student, & Team memberships available.