Delivers new analytics capabilities, extensive support for open source, and launches startup accelerator program
HP unveiled a series of new products, services, and programs designed to help organizations leverage data and analytics to build new products and experiences, run more efficiently, and differentiate against the competition.
The company announced a new release of HP Vertica, which will feature data streaming and advanced log file text search to power high-speed analytics on Internet of Things (IoT) data.
It also announced extensive support for and contributions to open source technologies, including optimized Hadoop performance, integration with the Apache Kafka distributed messaging system, and advancements in Distributed R predictive analytics.
The HP Haven Startup Accelerator program, which provides early-stage companies with fast, affordable access to both HP Big Data and Application Delivery Management software and services.
The announcements further accelerate HP’s differentiated big data strategy – around enabling organizations to harness data of all types, including emerging forms such Internet of Things device data, leveraging important new open source projects, and providing developers and early stage companies with the tools they need to become successful, data driven organizations.
“Developers are the new heroes of the Idea Economy,” said Vivek Ratna, Country Director, Big Data Platform. “HP is uniquely positioned to help businesses and developers thrive in this new world.”
HP has announced a new version of HP Vertica, the industry’s fastest SQL database, code named “Excavator”. Capabilities include Data streaming analytics, and Advanced Machine Log Text Search.
HP Embraces Big Data Open Source with Breakthrough Advances
HP also released a series of innovations that enable organizations to combine the innovation of open source with the enterprise-scale, reliability, and security of HP’s Big Data platform. These include HP Vertica for SQL on Hadoop native file support, HP Vertica Flex Zone Table Library, and Native Integration with Apache Spark.
