AtScale Releases Adaptive Analytics 2020.1

AtScale, the intelligent data virtualization provider for advanced analytics, is launching its Adaptive Analytics 2020.1, providing a leap in multi-cloud and hybrid cloud analytics, data platform flexibility and more.

Delivering on the promise of a single enterprise view of all analytics data, AtScale’s enhanced autonomous data engineering alleviates the performance and scale challenges of traditional data federation, manual data engineering and reliance on query caches.

Additional enhancements in AtScale 2020.1 include a virtual cube catalog for simplified management of data assets and granular policy control that integrates natively with existing enterprise data catalog offerings. 

“AtScale 2020.1 is a major step toward achieving our long-term vision of delivering intelligent data virtualization to every enterprise,”said Christopher Lynch, executive chairman and CEO of AtScale. “This release enables enterprises to alleviate the scale and performance limitations associated with their legacy analytics platforms and seamlessly embrace agile, hybrid cloud and multi-cloud data platforms, ensuring organizations have the ability to make informed decisions based upon all of their data.”  

The AtScale Adaptive Analytics 2020.1 platform release includes:

  • Multi-Source Intelligent Data Model - Create logical data models via an intuitive user experience without copying or transforming existing data structures. AtScale’s autonomous data engineering further simplifies and accelerates the user experience by assembling the data needed for queries in a just-in-time fashion and then maintaining acceleration structures for subsequent workloads.
  • Self-Optimizing Query Acceleration Structures - AtScale incorporated additional information into the creation and lifecycle of acceleration structures, including data locale and platform capabilities. AtScale alleviates the “lowest common denominator” approach to query planning that results in significant resources being wasted on manual data provisioning and movement. AtScale’s autonomous data engineering automatically determines the necessary structures and their optimal location.
  • Virtual Cube Catalog - AtScale’s new virtual cube catalog accelerates discoverability with comprehensive data lineage and metadata search capabilities that integrate natively into existing enterprise data catalogs. This new capability translates directly into business semantics and empowers business analysts and data scientists to locate the necessary data for business intelligence, reporting and AI/ML activities.

For more information about this release, visit