With Excel output, the Big Data crunching platform could become more appealing to smaller companies
Microsoft is developing a feature that will allow Excel users to import data from Apache Hadoop, the popular open-source storage and data analysis framework.
The connector is being developed in cooperation with Hortonworks, a team that has contributed more than 80 percent of all the code in Hadoop.
Bigger Data, Bigger Spreadsheets
Hadoop enables data-intensive distributed applications to work with thousands of nodes and exabytes of data. It also enables organisations to more efficiently and cost-effectively store, process, manage and analyze the growing volumes of data being created and collected every day. It can connect thousands of servers to process and analyze that data at supercomputing speed.
After six years in development, Hadoop has recently achieved the level of stability that allowed Apache to designate it as a release version 1.0.
Microsoft has already taken steps to make Hadoop compatible with its solutions. Last year, it released a Hadoop connector for SQL Server. It also offers connectivity to an instance of Hadoop on its Azure cloud service, currently as a developer preview only.
“As long-time contributors and supporters of Apache Hadoop, Hortonworks is proud to provide expert technical assistance and support that helps organisations such as Microsoft extend Hadoop to reach millions of new users,” said Rob Bearden, CEO of Hortonworks.
“Seamlessly combining the power of Apache Hadoop with existing Windows-based applications enables organizations to conduct deeper analysis of big data and make more intelligent business decisions,” he added.
Microsoft is not the only company interested in developing new features for the open-source platform. Business analytics software provider Birst has recently announced support for Hadoop. It will provide tools that will make the software more business-friendly, and usable by smaller companies.
Meanwhile, VMware has introduced Spring Hadoop – a project that will make it easier for enterprise Java developers to use the popular Spring Framework to build products around the Hadoop platform.
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