MapR Technologies, Inc. recently announced the industry’s first and only converged data platform and introduced MapR Streams, a reliable, global event streaming system that connects data producers and data consumers across shared topics of information. The MapR Converged Data Platform integrates file, database, stream processing, and analytics to accelerate data-driven applications and address emerging IoT (Internet of Things) needs.
The integration of MapR Streams into a converged platform enables organizations in any industry to continuously collect, analyze and act on streaming data. From advertisers providing relevant real-time offers, to healthcare providers improving personalized treatment, to retailers optimizing inventory, to telecom carriers dynamically adjusting mobile service areas, organizations must improve their responsiveness to critical events with the continuous analysis of big data.
According to Gartner, “Even as traditional workloads become progressively more optimized, entirely new ones are arising, notably from the emergence of IoT dataflows – that will dwarf previous volume and velocity demands and demand new stacks of hardware, networking and especially information management technology for processing, securing and distributing new varieties of data.”1
“MapR is at the forefront of designing solutions for data-centric businesses as they operate today and provides the best big data platform with a core architecture in place to successfully address modern data challenges,” said Michael Brown, CTO, comScore. “Our system analyzes over 65 billion new events a day, and MapR Streams is built to ingest and process these events in real time, opening the doors to a new level of product offerings for our customers.”
MapR Streams can easily scale to handle massive data flows and long-term persistence while providing enterprise features such as high availability (HA), disaster recovery (DR), security, and full data protection.
“We continue to be impressed with the innovative new features MapR has been integrating into its data platform,” said Brad Anderson, vice president, big data informatics, Liaison Technologies. “Our customers are in regulated industries such as healthcare and financial services, which have incredibly demanding security, compliance and agility requirements. We are seeing the converged MapR platform with MapR Streams delivering more real-time data services to our users, while enhancing those important criteria.”
Unlike other approaches that create data silos across multiple systems and lack the required enterprise-grade features and global replication, only MapR natively integrates data-in-motion and data-at-rest in one converged data platform. As a result, MapR enables developers to create new, innovative applications that reduce data duplication and movement, lower the cost of integration and maintenance associated with multiple platforms, and accelerate business results.
“Bringing together world-class Apache Hadoop and Apache Spark with a top-ranked NoSQL database and now continuous, reliable streaming with global scale is a huge step forward in enabling enterprise developers to create the next-gen apps using big data,” said Anil Gadre, senior vice president, product management, MapR Technologies. “MapR continues to execute on its vision of making it easy for enterprises to get the competitive edge from big data by bringing together all of the essential components.”
With MapR Streams, for the first time, developers can harness the power of a continuous, converged, and global data platform, allowing them to:
- Easily build scalable, continuous high-throughput streams across thousands of locations with millions of topics and billions of messages
- Unite analytics, transaction, and stream processing to reduce data duplication, latency, and cluster sprawl while using existing open source projects like Spark Streaming, Apache Storm, Apache Flink, and Apache Apex
- Enable reliable message delivery with auto-failover and order consistency
- Ensure cross-site replication to build global real-time applications
- Provide unlimited persistence of all messages in a stream
MapR works closely with numerous leading technology partners, such as data Artisans, Databricks, DataTorrent, StreamSets, and Syncsort, to provide customers with the flexibility to choose the components they want in their real-time analytics data platforms.
“MapR has fully embraced Apache Spark, and now with the scale, performance and flexibility delivered by MapR Streams, the solution is a great complement to Spark Streaming,” said Kavitha Mariappan, vice president, marketing, Databricks. “We look forward to our continued partnership with MapR and to offering our joint customers a powerful, converged data platform that simplifies the management of data in motion regardless of its source, location and format.”
MapR Streams will be generally available in early 2016.
About MapR Technologies
MapR provides the industry’s only converged data platform that integrates the power of the top-ranked Hadoop and Spark with global event streaming, real-time database capabilities, and enterprise storage, enabling customers to harness the enormous power of their data. Organizations with the most demanding production needs, including sub-second response for fraud prevention, secure and highly available data-driven insights for better healthcare, petabyte analysis for threat detection, and integrated operational and analytic processing for improved customer experiences, run on MapR. A majority of customers achieve payback in fewer than 12 months and realize greater than 5X ROI. MapR ensures customer success through world-class professional services and with free on-demand training that 45,000 developers, data analysts and administrators have used to close the big data skills gap. Amazon, Cisco, Google, HP, Microsoft, SAP, and Teradata are part of the worldwide MapR partner ecosystem. Investors include Google Capital, Lightspeed Venture Partners, Mayfield Fund, NEA, Qualcomm Ventures and Redpoint Ventures.
Gartner, “Predicts 2015: Information Infrastructure Technology Rewrites, Refreshes Rules, Merv Adrian et al., 19 December 2014