Pivotal is seeking to capitalise on the Big Data revolution with upgrades to its Pivotal Big Data Suite for enterprise.
The company announced the upgrades at EMC World in Las Vegas.
Pivotal used the conference to showcase major upgrades to its enterprise-grade Pivotal HD Apache Hadoop distribution and performance improvements for its analytic solutions including its Greenplum Database,
Pivotal vice president data product group, Sundeep Madra, said that as the cost of computing declines and connectivity becomes ubiquitous, enterprises will be challenged not only by the deluge of data created by applications and customer interactions, but from the billions of devices joining their networks.
“Pivotal's continued investments in the Big Data Suite allows enterprises to create true business impact by enabling apps that scale, analytics that predict behavior and prescribe actions and lastly, a realistic solution to their digital transformation aspirations.”
The firm said the advancements are designed to help customers manage ballooning data sets driven by mobile, Cloud, social, and the Internet of Things.
The major component upgrades to Pivotal’s Greenplum Database are touted as a major leap in performance with an enhanced Pivotal Query Optimizer, a cost-based query optimiser for Big Data.
It is said to give enterprise customers the ability to handle a large number of diverse workloads at high performance and enable large teams to simultaneously work on multiple analytics use cases.
Anchored in open-source software and based upon a subscription model, Pivotal Big Data Suite is said to scale up and support new and existing approaches to data architectures.
The platform now features Apache Hadoop 2.6 and Apache Ambari. Pivotal has also issued updates to existing Hadoop components for scripting and query including Apache Pig and Apache Hive.
It added a non-relational database, Apache HBase, along with basic coordination and workflow orchestration in the form of Apache Zookeeper and Apache Oozie.
Pivotal has also added Apache Spark core and machine learning library, additional Hadoop components for improved security, monitoring and data processing.
