PivotalBigDataSuite

Pivotal Big Data Suite Accelerates Digital Transformation with Upgraded Apache Hadoop Distribution

Major component upgrades bring up to 100x performance gain

Kuala Lumpur | Pivotal®, the company powering digital transformation for enterprises, announced significant updates to Pivotal Big Data Suite at EMC World which ran from 4 – 7 May 2015 in Las Vegas, Nevada.

This includes major upgrades to its enterprise-grade Pivotal HD Apache™ Hadoop® distribution, and up to 100x performance improvements for its analytic solutions, including Pivotal Greenplum® Database. Designed to help customers manage ballooning data sets driven by mobile, cloud, social, and the Internet of Things, these advancements help tackle the most complex queries across these data sets at unprecedented speed, scale, and flexibility.

Based on a subscription model and anchored in open-source software, Pivotal Big Data Suite delivers modern software designed to scale up and support new and existing approaches to data architectures.

Driving the significant performance gains of Pivotal Greenplum Database and Pivotal HAWQ®, is the new Pivotal Query Optimizer, the most advanced cost-based query optimizer for big data. Pivotal Query Optimizer has been proven to deliver significant performance boosts to Pivotal HAWQ, the world’s most advanced enterprise SQL on Hadoop engine, and to Pivotal Greenplum Database.

Pivotal Greenplum Database and Pivotal HAWQ

  • Major leap in performance with a massively enhanced Pivotal Query Optimizer, the most advanced cost-based query optimizer for big data;
  • Ability to handle a large number of diverse workloads at high performance enables large teams to simultaneously work on multiple analytics use cases;
  • Ability to handle big data volumes at scale without performance degradation;
  • Enhanced data structure and data management capabilities.

Pivotal HD

  • Now based on a standardised Open Data Platform core consisting of Apache Hadoop 2.6 and Apache Ambari;
  • Updates existing Hadoop components for scripting and query (Apache Pig and Apache Hive), non-relational database (Apache HBase), along with basic coordination and workflow orchestration (Apache Zookeeper and Apache Oozie);
  • Adds Apache Spark core and machine learning library;
  • Adds additional Hadoop components for improved security (Apache Ranger (incubating), Apache Knox), monitoring (Nagios, Ganglia in addition to Apache Ambari) and data processing (Apache Tez).

“Pivotal Greenplum Database’s new features are expected to maximise the utilisation of our hardware resources and provide better performance for complex queries on big data. This could enable us to shorten the time it takes to gain meaningful and trustworthy business insights and quickly act on them using existing assets.”

Sergey Sotnichenko, Head of Data Warehousing and Reporting, Tinkoff Bank

“As a long time Greenplum customer, we are excited to see Pivotal’s continued investment in the Greenplum Database. While the current product performs well, the new features will shorten the cycles of innovation by enabling complex queries on large data sets and bringing analytics closer to big data. ”

Zhang Min, Vice President, CITIC Bank

Pivotal

Pivotal is a trusted partner for digital transformation, enabling enterprises to provide modern software-driven experiences for their customers and workforces.

© 2015 Pivotal Software, Inc. All rights reserved. Pivotal, Greenplum and HAWQ are trademarks and/or registered trademarks of Pivotal Software, Inc. in the United States and/or other countries. Apache, Apache Hadoop, Hadoop, Apache Ambari, Apache Pig, Apache Hive, Apache HBase, Apache Zookeeper, Apache Oozie, Apache Ranger, Apache Knox, and Apache Tez are either registered trademarks or trademarks of the Apache Software Foundation in the United States and/or other countries. The ASF is not affiliated with the Open Data Platform initiative (ODP) and does not sponsor or endorse ODP. All other trademarks are the property of their respective owners.

Figure: Pivotal Big Data Suite





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