November 3, 2017

Xcalar provides a modern analytics platform through the Microsoft Azure Marketplace

More companies are embarking on a journey to become a data driven organization. They understand that extracting meaningful insights from a growing number of data sources provides an opportunity to be more competitive. Customers have many choices when it comes to selecting a modern analytics platform, however, the complexity to deploy these technologies can be overwhelming. Deploying new business applications in the cloud would reduce some of the challenges if it offers speed of deployment, operation, and scalability.

The partnership between Xcalar and Microsoft takes advantage of Azure Cloud Services to provide elastic, scale-out relational compute capabilities for customers. The Xcalar Data Platform, an open and extensible analytics platform, can be used by data engineers, data scientists, and business analysts to implement and manage the complete analytics pipeline. They can construct sophisticated data pipelines for petabyte-scale workloads by utilizing Xcalar’s user-friendly GUI.

Businesses who want to accelerate their big data analytics projects with modern enterprise grade tools, as provided by Xcalar, can now do so by quickly provisioning compute capacity in the Azure cloud. With Xcalar’s unique True Data In PlaceTM technology, customers can work directly from source data files, no matter where the data is stored, without copying them into an internal format as required by relational databases. For example, customers can run Xcalar on Azure to work with data stored on Azure, Amazon S3, Google Cloud Storage or on premises.

In addition, compute and storage can scale independently to meet their processing and storage needs for different types of sustained or burst workloads. All this makes Xcalar Data Platform on Azure a unique big data analytics solution in the cloud.

Seeing is believing, so the saying goes. That is why Xcalar offers new customers a two week free trial, so that they experience first hand how easy big data analytics can be.

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Yves Laurent
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