According to a recent press release, “AtScale, the data warehouse virtualization company, today announced its new 2019.2 platform release. The latest release augments AtScale’s autonomous data engineering innovations with the introduction of a sophisticated time-series and time-relative analysis capability for large volumes of data across disparate databases and platforms. This new capability enables data analyst and data science teams to have unencumbered access to large volumes of dispersed operational time-series data. Data consumers can quickly query and configure data for their specific business definitions using the business intelligence (BI), artificial intelligence (AI) or machine learning (ML) tools of their choice. AtScale enables scalable and governed self-service analytics, utilizing its native security and performance functionality, with no need to move data or perform memory limited operations.”

The release goes on, “Leveraging the high performance optimization technologies developed by AtScale for distributed shared-computing platforms such as Hadoop, AtScale continues to make significant advancements in the virtualization of data platforms, now including Teradata, Oracle, Snowflake, Redshift, BigQuery, Greenplum, and Postgres. ‘We’ve built on over 150 combined person-years mastering the challenges of on-premise and cloud data platforms to reinvent how enterprise teams drive performance for multidimensional analytics,’ shares Matthew Baird, co-founder, and CTO of AtScale. ‘For companies to manage big data at the scale, complexity and security enterprises require, AtScale has completely reinvented how analytical queries are answered, taking full advantage of the various platforms’ native optimizations’.”

Read more at Globe Newswire.

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