XENON has partnered with Vertica to offer its Analytics Platform with its Machine Learning and Advanced Analytics capabilities delivering performance at Exabyte scale.
Vertica is designed for use in data warehouses and other big data workloads (including real-time streaming data) where speed, scalability, simplicity, and openness are crucial to the success of analytics.
Vertica is Data Analytics without Limits and is built on a proven columnar storage compression, reliable distributed architecture to deliver a best-in-class, unified big data analytics platform that will forever be independent from underlying infrastructure. The capability to deploy anywhere delivers on the promise of big data analytics like no other solution.
XENON partnering with Vertica can design, build and deploy an end-to-end analytics platform that enables customers to monetize their data and gain valuable insight into the business.
Customer success stories with Vertica analytics platform include global deployments across Healthcare, Retail, Telco, Financial Services (BFSI), Utilities, Marketing and Infrastructure clients.
The Vertica Analytics Platform purpose built from the very first line of code for Big Data Analytics, provides you with the broadest range of deployment models, so that you have complete control and choice as your analytical needs evolve:
- Vertica Enterprise: The core “shared nothing,” distributed analytical database designed to work on clusters of cost-effective, off-the-shelf servers in your data center with unparalleled performance and extreme scale.
- Vertica in the Clouds: Optimized and pre-configured to run on AWS, Microsoft Azure, Google and VMware clouds, Vertica is also available as a BYOL (Bring Your Own License) model to enable you to transition your data analytical workloads to the cloud to on premise and back seamlessly.
- Vertica for SQL on Hadoop: Run the industry’s most comprehensive Vertica SQL analytics engine directly on your Hadoop cluster and tap into advanced SQL on Hadoop capabilities, complete 100 percent of the TPC-DS queries without modification, achieve greater concurrency, and run on any Hadoop distribution.