Returning to the fundamentals of database management is crucial as the technical world continues to evolve at a rapid pace. Examining core database infrastructures, as well as the new technologies and challenges shaping them, will prepare the enterprise for the paradigms to come.
DBTA’s latest webinar, The Next Era of Database Management: Emerging Technologies and Best Practices, featured the viewpoints of database experts from Datavail and Oracle, covering topics such as cloud native databases, database types, vendor lock-in, AI, optimization, and more.
The current data management landscape is lagging behind its pace of innovation, according to Srinivasa Krishna, director and global practice lead of MySQL services at Datavail. Sixty-two percent of organizations are still at basic data management maturity level, with only 8.3% being mature enough to leverage AI for insights, assistance, and recommendations, according to DBTA’s 2024 Market Study.
This general lack of readiness contradicts the industry sentiment that everyone is adopting and succeeding with AI—whereas the former may be true, but the latter is debatable. With certain data challenges still prevailing—such as performance, cost optimization, and scalability—the likelihood that enterprises are ready for advanced initiatives such as AI is low.
These challenges surface when traditional databases are used to support modern workloads. Their lack of scalability leads to performance bottlenecks, noted Anuj Pandey, senior Oracle database administrator at Datavail, which lead to enterprises procuring more CPUs and more memory—ultimately increasing costs and maintenance complexity.
Mike Frank, MySQL product management director at Oracle, added that security challenges are equally as pertinent. Traditional databases introduce significant friction, especially in regard to identity management, which is compounded by the complexities of cross-team collaboration.
“No longer can you just look at [databases] at a single point,” said Frank. “Having silos of data all over the place is a problem, especially when you need to join that data together to do some sort of analysis…a lot of these challenges require standardization.”
Another facet of modern workloads is the need for diverse data type support, from structured to semi-structured and unstructured. Freddy Hernandez, multi-cloud database leader at Oracle, noted that different data types is not the main complexity; the complexity lies within its management. The maintenance and management of different systems and applications that are needed to communicate with different types of data is where challenges arise.
“That’s why you need to start thinking of how you can start combining some of those systems that support different data types,” said Hernandez. “Here at Oracle, that is what we call a converged database…[it] gives you the flexibility in the type of data you handle.”
From support for spatial data to IoT, as well as for different types of architectures such as distributed databases or microservices, is the vision for the future of databases, according to Hernandez. Frank added that it’s not only diverse data types that need attention, but the different types of processing performed on that data, such as real-time processing. Persistence of data across systems without overloading the database itself is crucial.
This is only a snippet of the thought-provoking discussion from the Datavail and Oracle experts. For the full, in-depth examination of modern database management, you can view an archived version of the webinar here.