MapR
Powering Hadoop Applications for Real-Time Data

“The creation of Hadoop and the beginning of the big data era traces its roots back to the Google white paper on the MapReduce framework; the MapR name is an acknowledgement of these roots,” says Jack Norris, Chief Marketing Officer, while talking about the rationale behind the company.

Headquartered in San Jose, CA, MapR delivers on the promise of Apache Hadoop with a proven, enterprise-grade platform that supports a broad set of mission-critical and real-time production uses. The MapR Distribution for Hadoop combines over a dozen open source packages such as Apache Mahout, Spark, Hive, Pig and ZooKeeper, with MapR innovations to provide a differentiated Hadoop platform to address enterprise customer applications and uses. It was engineered for the data center with IT operations in mind. MapR enables Hadoop to serve business critical needs for big data applications that cannot afford to lose data and require immediate recovery from node and site failures. It supports these capabilities for the broadest set of Hadoop applications from batch analytics to interactive querying and real-time streaming. “The MapR Data Platform is a modern, true read-write capable, NFS-mountable distributed file-system written in C++ that directly accesses storage hardware—dramatically improving performance and ease of administration. It is also built to process both distributed files and database tables in one unified layer,” says Norris.

To store and process big data, MapR provides a wide range of enterprise-grade capabilities. MapR offers multiple editions of its Hadoop distribution. M3 is the Standard Edition that can be downloaded for free and has unlimited production use. It includes performance advantages, advanced management console, and standard file access. The M5 Enterprise Edition enables full data placement capabilities for increased security, speed and manageability and powers Hadoop applications that meet stringent high availability SLAs even under disaster recovery conditions. The M7 Enterprise Database Edition enables continuous real-time operations and handles high-volume and high-velocity database workloads with batch analytical tasks.

It supports a column-oriented NoSQL data model to manage a wide variety of operational data formats and is compatible with the Apache HBase core API for running existing HBase and M7 online database in the same cluster.

MapR enables Hadoop to serve business critical needs for Big Data applications that cannot afford to lose data and require immediate recovery from node and site failures

Numerous customers such as Samsung, Beats Music, HP and Cisco across different industries like financial services, retail, media, healthcare, manufacturing, telecommunications, government organizations as well as Fortune 100 and Web2.0 companies uses MapR. One of its clients Return Path, an email intelligence software company, had been the early implementer of Hadoop and it needed a Hadoop platform that would help them to take the experience to the next level and get most from their investment in Hadoop. With the help of MapR, Return Path discovered that higher density nodes required much less administration on MapR, allowing them to manage nodes of 20 terabytes versus 6 terabytes with their previous solution. It has helped Return Path to gain enterprise grade capabilities and reduced administrative costs from MapR.

The company is investing engineering resources for data agility by decreasing time to value from data, including investing heavily in open source projects such as Apache Drill. “Apache Drill is the only interactive SQL project that is architected for both centrally structured and self-escribing data. Drill supports the query of data structured in HCatalog, but also can query data structures using data-interchange formats like JSON,” says Norris.