MapR - News, Features, and Slideshows

News

• HPE plus MapR: Too much Hadoop, not enough cloud

  Cloud killed the fortunes​ of the Hadoop trinity - Cloudera, Hortonworks and MapR - and that same cloud likely won’t rain success down on HPE.

• IBM commits to Apache Spark compute engine

  Calling Apache Spark "the most important new open source project in a decade that is being defined by data," IBM today announced that it will embed the compute engine into its analytics and commerce platforms and offer Spark as a service on IBM Bluemix.

• Cascading big data framework gets Apache Tez support

  After about a year-and-a-half of development, big data application platform specialist Concurrent today released a new version of the open source Cascading big data application framework.

• MapR 5.0 Hadoop supports real-time applications

  With a focus on real-time applications, MapR Technologies took the wraps off the 5.0 version of its Hadoop distribution.

• Pentaho adds Amazon EMR, SAP HANA to data integration platform

  On the heels of Hitachi Data Systems (HDS) closing on its acquisition of data integration specialist Pentaho last week, Pentaho today released an update to its platform that adds integration for Amazon Elastic MapReduce (EMR) and SAP HANA.

• MapR adds self-service SQL Analytics

  MapR Technologies updated its Hadoop distribution today to support self-service SQL analytics.

• Pentaho adds orchestration for Apache Spark jobs

  In the past several years, Pentaho Labs, the research arm of business analytics specialist Pentaho, set out to map the various big data use cases organizations were putting into production as part of an effort to provide big data blueprints, a big data stack if you will.

• Can a startup democratize big data apps?

  Imagine a data platform that makes it easy for line-of-business users and data scientists to extract insights, as well as share and collaborate on them, from all data sets -- big and small -- for real-time decision making. All employees, regardless of technical background, would be able to utilize the same information without the need to restructure data for any specific query.

• Teradata brings MapR Hadoop into the data warehouse

  Enterprise data sets have gotten so voluminous that they can't fit into even the largest data warehouses anymore, many businesses find. Now, companies running these overstuffed data stores have an on-ramp to newfangled, big-data style processing through a combined effort between analytics systems supplier Teradata and Apache Hadoop distribution provider MapR.

• Glassbeam Integrates Its IoT Analytics Platform with Spark

  With an eye toward enhancing its Internet of Things (IoT) analytics platform with advanced machine learning and real-time analytics capabilities, machine data analytics specialist Glassbeam today released a new version of the platform that tightly integrates it with Apache Spark.

• MapR Makes Its NoSQL Database Freely Available in Community Edition

  At O'Reilly Strata Conference + Hadoop World 2014 in New York City today, Hadoop distribution specialist MapR Technologies announced that its MapR-DB NoSQL key-value database is now available for unlimited production use as part of its free MapR Community Edition.

• Hadoop distributor MapR gets $110M from Google

  MapR, which distributes a commercial software platform based off the Apache Hadoop big data management open source project, has secured a $110 million funding round led by Google.

• Nine Hadoop companies you should know

  If you've got a lot of data, then Hadoop either is, or should be on your radar.

• Big Data skills pay top dollar

  If you're in tech, it pays to be in big data. Nine of the top 10 highest paying IT salaries are for languages, databases and skills related to big data.

• Big Data Application Framework Gets Update, SQL Interface

  Open source big data application platform specialist Concurrent has released a new version of the Cascading application framework and simultaneously released Cascading Lingual 1.0, an ANSI SQL interface for Hadoop.