Cazena announced Big Data as a Service offering data marts and data lakes on Microsoft Azure, integrated directly into enterprise infrastructure. Customers get on demand cloud data processing that works easily and securely with their existing tools.
Many enterprises want to speed up analytics and reduce costs by using the cloud for big data and data warehousing, and are seeking a secure connection to the cloud with a low investment in development and process change including time, budget, and specialized resources.
We see accelerating demand from enterprises wanting to broaden their adoption of the cloud to data warehousing and big data processing,” observed Prat Moghe, Cazena Founder and CEO. “Our launch on Microsoft Azure extends Cazena’s vision of big data on demand for enterprises.”
Cazena’s service further bridges the gap between cloud and enterprise. Its unique architecture uses a secure big data gateway to connect existing analytic tools and systems to Azure without disrupting data flow or requiring a big development project. With Cazena, customers can extend data warehouse investments by offloading workloads to the cloud, easily analyze big data sources originating outside their network like social media and IoT, and drive faster data science outcomes.
Cazena will help accelerate customers’ ability to migrate big data workloads to Microsoft Azure,” said Steve Guggenheimer, Corporate Vice President and Chief Evangelist, Developer Experience, Microsoft Corp. “The combination of trusted infrastructure and price-performance leadership of Azure, with Cazena’s service, will help simplify big data processing for organizations looking to utilize the cloud.”
Cazena’s platform incorporates multiple, best of breed database engines. As part of this release, Cazena added support for the Greenplum Database to its cloud data mart offering. Leading Hadoop distributions such as Cloudera already power Cazena’s cloud data lake offering. Having both data mart and data lake services on a single cloud platform provides a complete analytic pipeline for customers.
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