MapR Awarded Patent for Converged Data Platform

Company lays claim to optimal architecture for big data

MapR Technologies has been granted a patent (US9,207,930) from the United States Patent and Trademark Office. The awarded patent recognizes the company’s fundamental innovation in data architecture that enables real-time and mission-critical application deployments at scale. The patented MapR Platform eliminates data silos through the convergence of open source, enterprise storage, NoSQL, and event streams with unparalleled performance, data protection, disaster recovery, and multi-tenancy features.

“The patent details the highly differentiated capabilities of our platform which give us an ongoing technology advantage in the big data market. Some of the most demanding enterprises in the world are solving their business challenges using MapR,” said Anil Gadre, senior vice president product management, MapR Technologies. “This is also a great example of how foundational innovation can be combined with open source to enable customers to gain a competitive advantage from the power of a converged data platform.”

The key components of the patent claims include:

  • An architecture based on data structures called “containers” that safeguards against data loss with optimized replication techniques and tolerance for multiple node failures in a cluster
  • Transactional read-write-update semantics with cluster-wide consistency
  • Recovery techniques which reconcile the divergence of replicated data after node failure, even while transactional updates are continuously being added
  • Update techniques that allow extreme performance and scale while supporting familiar APIs

Leveraging these inventions, the MapR Converged Data Platform delivers a core architecture for data-centric businesses along these four key areas:

Innovating with open source – A differentiated core with standard APIs drives greater value from the many available Apache projects. Advanced technologies allow greater scale and performance while compliance with community-driven open APIs such as industry standard POSIX, NFS, LDAP, ODBC, REST, and Kerberos allows all of the key open source big data systems to work with existing systems.

Foundation for converged analytics – A platform that enables multiple workloads in a single cluster lets customers run continuous analytics on both data at rest and data in motion without the delay due to moving data to a task-specific cluster. Having a single cluster that can handle converged workloads is also easier to manage and secure.
Enterprise-grade reliability in one platform – Built-in high availability, disaster recovery, data recovery, and security features let customers run big data apps leveraging Hadoop, Spark and other open source projects in a business-critical, 24×7 environment that must never lose data.

Real-time, continuous data processing – Full read-write capabilities, low administration, automated optimizations, and immediate access to data all enable an end-to-end real-time environment that lets analysts continuously leverage data for gaining critical business insights.

Testing big data in development environments is dramatically different from deploying it into production. Adding to a growing IP portfolio, this patent demonstrates the MapR commitment to helping customers maintain SLAs through reliability and disaster recovery. The MapR Converged Data Platform ensures production success with an architecture designed specifically for business-critical applications, seamless data access and integration, and the ability to run both operational and analytical processing and applications reliably on one platform.

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