MapR Technologies launches Apache Hadoop Application Gallery

Showcases solutions to help customers gain maximum value from big data deployments.

MapR Technologies, Inc has launched at what it says is the industry’s first Hadoop application gallery. Launching with solutions from a wide range of Hadoop ecosystem partners, the MapR App Gallery is designed to help customers derive greater business value from big data as they scale-out their enterprise data architectures.


Aimed at end-user developers, administrators, and analysts who want to develop more sophisticated big data capabilities to enhance their business operations and decision-making, the MapR App Gallery offers the benefit of ready-made big data utilities and applications.


“Our customers typically run many different applications on a MapR cluster and the App Gallery makes it much easier and faster to achieve success,” said Jack Norris, chief marketing officer, MapR Technologies. “There is already a broad range of applications available, and we anticipate the number of applications will grow – particularly those leveraging unique capabilities that enable customers to better optimize revenue, control costs and mitigate risk.”


The App Gallery includes administrator-oriented apps for provisioning, management, and security; developer-oriented applications, query engines and frameworks; and analyst-focused applications for business intelligence and machine learning. Partners and solutions represented in the MapR App Gallery today include:
· Database: Hadapt, HP Vertica, Rainstor, and Splice Machine
· Analytics and Data Integration: Alpine Data Labs, Appfluent, Data Tactics, Datameer, DataTorrent, Informatica, Information Builders, Jaspersoft, Pentaho, Platfora, Revelytics, Revolution Analytics, Syncsort, Tableau, and Talend
· Search: Elasticsearch and LucidWorks
· Machine Learning: 0xdata, Skytree, and Zementis
· Management and security: Dataguise, Splunk, StackIQ, and Voltage


The MapR Distribution is the most open distribution for Hadoop with industry-standard APIs to make it plug-and-play without special-purpose connectors or porting. Developers are encouraged to participate by leveraging one or more of the following open interfaces in their applications:
· Storage access via HDFS API and NFS
· Job execution via YARN, Tez, MapReduce, and Spark
· Ecosystem interfaces including HBase, HiveQL, PigLatin
· SQL via Drill, Hive, Stinger/Tez
· Administration interfaces including REST
 

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