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5 best tools for Big Data

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Rajkumar Maurya
New Update
BIG DATA

Jaspersoft BI Suite:

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The Jaspersoft package is one of the open source leaders for producing reports from database columns. The company  adding a software layer to connect its report generating software to the places where big data gets stored. Hadoop is also well-represented, with JasperReports providing a Hive connector to reach inside of HBase. The JasperReports Server now offers software to suck up data from many of the major storage platforms, including MongoDB, Cassandra, Redis, Riak, CouchDB, and Neo4j.

Jaspersoft BI Suite

Pentaho Business Analytics:

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Pentaho tightly couples data integration with business analytics in a modern platform that brings together IT and business users to easily access, visualize and explore all data that impacts business results. Use it as a full suite or as individual components that are accessible on-premise in the cloud or on-the-go (mobile). Pentaho Kettle enables IT and developers to access and integrate data from any source, and deliver it to your business applications, all from within an intuitive and easy to use graphical tool.

Pentaho Business Analytics

Karmasphere Studio and AnalystIt is a set of plug-ins built on top of Eclipse. It's a specialized IDE that makes it easier to create and run Hadoop jobs.

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Karmasphere Studio and Analyst

Talend Open Studio: It provides integration that truly scales. From small projects to enterprise-wide implementations, Talend’s highly scalable data, application and business process integration platform maximizes information assets and development skillsets. Ready for big data, Talend’s flexible architecture adapts to future IT platforms. Talend also offers an Eclipse-based IDE for stringing together data processing jobs with Hadoop.

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Tableau Desktop and ServerTableau Desktop is a visualization tool that  is optimized to give you all the columns for the data and let you mix and makes it easy to look at your data in new ways. Tableau Software started embracing Hadoop and it relies upon Hive to structure the queries, then tries its best to cache as much information in memory to allow the tool to be interactive. Caching helps deal with some of the latency of a Hadoop cluster.

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