Inside Advanced Scale Challenges|Friday, April 28, 2017
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Oracle Fleshes Out Cloud Data Strategy 

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Oracle has made a lot of noise over the last six months or so intended to challenge public cloud services leaders, especially Amazon Web Services. It is now attempting to flesh out that vision with the introduction of a cloud service designed to integrate data with real-time analytics.

The cloud services challenger (NYSE: ORCL) on Monday (Feb. 13) rolled out a data integrator cloud service designed to accelerate support for real-time analytics across enterprises. The service addresses the shift of more data to the cloud and the resulting challenge of delivering the results of data analytics to the appropriate applications and the employees using those apps.

The data integration service targets data originating from the Internet of Things, web data, business applications as well as data stored in the cloud or on premises, the company said. The cloud service also integrates data where it is stored, "with no hand coding required, and without having to copy data unnecessarily" to remote locations, added Jeff Pollock, Oracle's vice president of product management.

As part of its "pushdown data processing" feature, the company argues that a souped up data extract, transform and load (ETL) capabilities reduce data movement, which it asserts is "best for the cloud." Meanwhile, alternative E-LT (extract, load, transform) workloads can be executed in Oracle's database and big data cloud services.

In order to accelerate movement of data between Oracle's and other platforms and applications, the cloud services platform includes integration with external big data tools such as HBase, HDFS, Hive and Sqoop. The company said the integration tool's mapping capabilities are designed to make it easier to switch between underlying analytics technologies without hand coding.

The automation of those tasks along with reduced network traffic is intended to boost cloud services performance along with side benefits such as reduced development costs, the company asserts.

The cloud data integration service is Oracle's latest salvo in the stiffening competition among cloud providers seeking to chip away at the leading position of public cloud powerhouse AWS (NASDAQ: AMZN). Database analytics competitors such as Cloudera and Oracle have been challenging AWS in areas such as data warehousing.

Larry Ellison, Oracle's cofounder and CTO, claimed last fall that Oracle Cloud was more than 100 times faster for database analytics than Amazon Redshift. The broadside was part of a larger Oracle campaign aimed at challenging public cloud leader AWS with an expanded analytics package that includes applications, infrastructure and database analytics.

The strategy also seeks to seize on the growing number of enterprises that use multiple cloud vendors, matching distributed applications and workloads to different cloud platforms to boost performance and reap savings while at the same time avoiding vendor lock-in.

For its part, Oracle launched a new cloud strategy last September that emphasizes an “elastic analytics platform” that combines Hadoop, Apache Spark and Kafka-based data streaming to create clusters for processing data with MapReduce and Spark, the company said.

About the author: George Leopold

George Leopold has written about science and technology for more than 25 years, focusing on electronics and aerospace technology. He previously served as Executive Editor for Electronic Engineering Times.

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