MapR Technologies recently announced breakthrough database innovations for data-intensive applications. MapR-DB enables context-rich applications, in-place and continuous machine learning/AI and SQL capabilities, and global real-time data integration and microservices support.
Below is our interview with Jack Norris, Senior Vice President, Data and Applications at MapR Technologies:
Q: Tell us about MapR-DB and how MapR continues to push the boundaries of data management?
A: As organizations aspire to build these applications, they need critical technology building blocks. Databases are the foundational components of application architecture in operationalizing the data. Our customers are trying to move after-the-fact insights and processes to real-time processes and in-the-moment proactive actions by infusing machine learning and AI driven data intelligence. Data is the foundational enabler in all these data-intensive applications. MapR-DB enables faster time-to-market, always-on intelligent business processes and contextual user experiences. MapR-DB supports multiple data models (document, wide column, key value, etc.) and unifies operations and analytics for in-place and continuous real time business insights. MapR-DB can operate thousands of mission critical next gen applications with consistent ultra-low latencies and high scalability.
Q: How do these product advancements relate to digital transformation?
A: Our customers are making big bets on modernizing the core business processes, uncovering real-time insights, and enabling automated decision making to cut down costs and innovate faster. Digital transformation starts with providing rich contextual user experiences to attract, engage, and retain key stakeholders. Enabling this business transformation requires organizations to scale data and applications. These data-intensive applications need the ability to capture and interact with diverse types of data including fast growing IoT data.
Q: What is most important feature and/or benefit of this new release?
A: The power and flexibility in our new release ushers in a new era of intelligent data-intensive business applications. Customers can now build applications that integrate operations and analytics, offer analytics as a service, embrace IoT and modernize core business apps. Because MapR-DB is part of our converged data platform, there are no tradeoffs when it comes to scale, performance and reliability.
Q: Tell us about MapR’s cloud vision.
A: Organizations start their cloud journey in different places and with different needs in mind. A key driver is the agility that comes with being able to spin instances up and down, but while bursting compute to the cloud stateful applications that rely on large data sets is more problematic. MapR provides the underlying data fabric to handle data at scale across locations whether that is on-premise to cloud or multiple clouds. This provides the ability to deploy applications across locations all the way to the edge and to optimize for cost, performance and government compliance.
Q: There has been a lot of buzz around the term data fabric. What is MapR’s take?
A: MapR takes it from a whole cloth perspective for a data fabric that represents a converged view of how to have a scalable, flexible solution that converges capabilities across data types, processing, and locations including cloud, on-premise and the edge. MapR provides the mechanism for customers to build a unified data fabric that stretches from edge devices, into the data center, and across public clouds.
This is in contrast to ETL vendors who define data fabric in terms of the connected movement and transformation of data between sources and destinations, or storage vendors are recasting some of their solutions in terms of data fabric that stretches their current capabilities. Each of these solutions is targeted at a different function and level in an organization from data administrators to storage administrators to enterprise architects. MapR introduced MapR-XD to allow users to create global data fabrics which are inherently ready for analytical and operational applications.Activate Social Media: