Pivotal Announces Upgrades to Big Data Suite

May 5 — Pivotal, the company accelerating digital transformation for enterprises, today announced significant updates to Pivotal Big Data Suite. 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, which comes with the most advanced, cost-based, Pivotal Query Optimizer for big data. These advancements are designed to help customers manage ballooning data sets driven by mobile, cloud, social, and the Internet of Things, and to tackle the most complex queries across these data sets at unprecedented speed, scale, and flexibility.

Mastering big data, agile methodologies, and cloud native applications are key elements to digital transformation for modern enterprises. Anchored in open-source software and based upon a subscription model, Pivotal Big Data Suite delivers modern software designed to scale up and support new and existing approaches to data architectures. In a single suite, Pivotal provides all of the data processing, analytics, and application capabilities to help enterprises gain better insights and create better user experiences, with the stability and security they require.

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 to deliver significant performance boosts to Pivotal HAWQ the world’s most advanced enterprise SQL on Hadoop engine, and to Pivotal Greenplum Database.

Pivotal Big Data Suite delivers the first version of Pivotal HD based on an Open Data Platform (ODP) core and includes major updates to Apache Hadoop components, including Apache Spark. Pivotal Big Data Suite is designed to provide customers with better stability, management, security, monitoring, and data processing capabilities in the Hadoop stack. This allows enterprises to off-load more business-critical workloads to Hadoop, to store and process large volumes of data at lower costs and in way that is compliant with policies and regulations.

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 standardized 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).