Enterprise-class database VoltDB announced that it is joining forces with AI and analytics platform MapR Technologies.
VoltDB provides real-time intelligent decisions on streaming data, while MapR Technologies provides the industry’s next generation data platform for AI and Analytics, which enables organizations to automate more intelligent decision-making with machine learning.
Through the joint solution, VoltDB will provide a real-time application database that will be used in conjunction with the MapR-FS file system to derive analytics and results from data streams based on machine learning algorithms. These will be embedded directly within the database infrastructure. With an underlying data platform that scales to meet large workloads, MapR provides a read-write file system that brings dependability, ease-of-use, and speed to the VoltDB database and its streaming applications.
By continuously exporting processed streaming data from VoltDB to the MapR-FS file system and importing trained machine learning models back, enterprises can immediately apply new insights to drive business outcomes. This is particularly beneficial to businesses, as large volumes of data constantly streaming in from multiple sources at a steadily high velocity. It is important that the machine learning models continually ingest and operationalize information in real-time with low latency.
“This VoltDB and MapR partnership allow our enterprise customers to apply MapR’s AI and Analytics data management on incoming data streams in VoltDB for their real-time decisions, creating significant business value for them,” said Geneva Lake, VP of worldwide alliances and business development at MapR.
“Just four percent of organizations that claim real-time decision-making is actually using machine learning, leaving room for doubt around the accuracy of the insights fueling decisions,” said David Flower, CEO of VoltDB. “The combination of VoltDB and MapR is ideal, allowing customers to make and understand more intelligent decisions in just milliseconds.”
