Today Pivotal Software Inc. announced major updates to its Pivotal Big Data Suite. The new updates include upgrades to Pivotal HD Apache Hadoop distribution and Pivotal is claiming up to a 100 times performance improvement for its analytics solutions, including Pivotal Greenplum Database. The new upgrades are aimed at helping 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.
Today Pivotal Software Inc. announced major updates to its Pivotal Big Data Suite. The new updates include upgrades to Pivotal HD Apache Hadoop distribution and Pivotal is claiming up to a 100 times performance improvement for its analytics solutions, including Pivotal Greenplum Database. The new upgrades are aimed at helping 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.
Modern enterprises need to be able to master Big Data, agile methodologies, and cloud native applications. This is where Pivotal Big Data Suite comes in. Based on a subscription model and anchored in open-source software, Big Data Suite is designed to scale up and support new and existing approaches to data architectures. Customers gain all of the data processing, analytics, and application capabilities they need in order to gain better insights in a single suite. Pivotal Big Data Suite is open, agile, and cloud read and its components can be deployed on commodity hardware, pre-certified appliances, virtualized and private cloud instances, and in public clouds
One of the new updates is the new Pivotal Query Optimizer, an advanced cost-based query optimizer for big data. The new optimizer is driving performance gains in both Pivotal Greenplum Database and Pivotal HAWQ. Another update is the first version of Pivotal HD, based on Open Data Platform core and includes major updates to Apache Hadoop components, including Apache Spark. This gives customers better stability, management, security, monitoring, and data processing capabilities in the Hadoop stack and enables them to off-load more business-critical workloads to Hadoop, lower costs while staying compliant with policies and regulations.
New benefits include:
- 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).
Availability
The new capabilities are available now.
