"Customers have made it clear that traditional approaches to managing and processing data for AI and Analytics leave critical gaps. In response, Map R’s newest innovations enable data scientists and developers to power distributed AI and analytics by leveraging all data for more impactful results,” said Anoop Dawar, senior vice president product management and marketing, Map R. “The continual evolution of the Map R platform is evident in this rich release of new capabilities, built in close collaboration with leading customers, to provide a multi-temperature, multi-protocol on-prem, edge and cloud data platform.”

“Integration and data management are at the heart of our advanced Liaison Alloy Platform which is designed to solve complex business problems for large global enterprises in healthcare, financial services and other industries. The Map R Data Platform is fundamental to Alloy’s ability to enable a seamless flow of data securely and at scale for our customers,” said Larry Mieldezis, CIO, Liaison Technologies. “We look forward to the new AI and Analytics capabilities which will provide exciting new advancements to our customers while significantly simplifying security and storage requirements for our Alloy Platform.”

The major platform update from Map R includes key areas of innovation that for the first time extend the data fabric to cloud storage through object tiering; fast ingest erasure coding for more cost-effective, long-term data retention; security innovations to automatically enable security across the environment, a new S3 API supporting next-gen applications and increasing application portability; and a wide array of analytical and real-time streaming enhancements.

A recent Gartner research note states the need for a new approach citing that “Data growth has far outstripped compute growth, resulting in an imbalance in system architectures. Emerging data-intensive workloads that require data-centric processing — such as AI, high-performance computing (HPC) and IoT — will expose the system imbalance, especially in data movement, resulting in new architectural innovations to address this gap.”