MapR advances MapR-DB for rich data-intensive applications and in-place analytics

MapR Technologies has introduced 'breakthrough' database innovations for rich data-intensive applications. With new advancements for developers that enable rich applications, in-place and continuous machine learning/AI and SQL capabilities, and global real-time data integration and microservices support, MapR continues to push the boundaries of data management.

 

“Xactly’s SPM Suite, predictive analytics and big data intelligence are the foundation for the sales programmes of more than a 1,200 customers. Billions of transactions flow through our systems each quarter and we have handled more than $20 billion in incentive compensation payments in the last two years alone,” said Ron Rasmussen, CTO, Xactly Corporation. “If our systems aren’t running at maximum performance, the course of business slows and people don’t get paid. MapR understands that our database architecture is critical to our success and that of our customers. Their system provides the flexibility and integrated analytics required for Xactly to continue to build and scale SPM solutions that are unmatched in performance, scalability and uptime.”

 

As part of the MapR Converged Data Platform, 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.

 

“Retro-fitting legacy databases in today’s big data environments presents challenges to organisations such as poor data performance, scale limitations, and data access restrictions.” said John L Myers, managing research director, Enterprise Management Associates, a Boulder, Colorado, based industry analyst firm. “Leveraging a one platform architecture, MapR Converged Data Platform enables organisations to efficiently process all data types bringing analytics and operations together with consistent scale, reliability and performance.  Specifically, MapR-DB capabilities help companies build a global multi-master database extending from the cloud to the edge and on-premises, accelerating data iterations and integrations for deploying next-generation online and mobile apps.” 

 

MapR-DB : bringing together operational, analytical and real-time applications

New database features in MapR-DB include:

·         Powerful data access with native secondary indexes

·         Rich application development with OJAI 2.0 APIs and smart query execution

·         In-place self-service SQL data exploration and operational BI with optimised Drill integration

·         Real-time processing and machine learning with native Spark and Hive connectivity

·         Real-time application integration with global change data capture

“At Xing, we are building a world-class business networking platform for millions of users for a better working life,” said Mustafa Engin S?zer, senior BI architect - Business Intelligence Competence Center, Xing. “We create massive amounts of data across multiple systems and being able to analyse all data in this fast-paced environment is key to serving our members better. MapR-DB allows us to converge data from various applications and technologies to create a self-service BI architecture. With consistently high performance, schema flexibility, and native integration with Apache Drill and Apache Spark, MapR-DB is empowering our architecture and allowing us to build real-time BI services.”

“The power and flexibility in our new release brings together the best of RDBMS and NoSQL ushering a new era of intelligent data-intensive business applications. Customers can now build single views of the business, offer analytics as a service, embrace IoT and modernise core business apps,” said Anoop Dawar, vice president, product marketing and product management, MapR Technologies.  “There are no tradeoffs when it comes to scale, performance and reliability.  Because MapR-DB is part of one platform, customers can contextualise user experiences by bringing together operational and analytical applications.”