AtScale Identified as an “Outperformer” in the GigaOm Radar for Data Virtualization
On November 24, 2020, Andrew Brust and Yiannis Antoniou published the GigaOm Radar for Data Virtualization report. AtScale was identified as an “Outperformer” in the report. GigaOm’s analysts cited AtScale’s strengths as “Excellent semantic layer capabilities. Automated data engineering based on observed data and user patterns. Good governance and metadata features.”
GigaOm points out that AtScale is a great fit of organizations wanting to develop a self-service data culture. The report also puts a focus on AtScale’s strong adherence to dimensional modeling and a semantic layer being a strength for many enterprise organizations. Other key highlights of AtScale in the report include:
- Easy-to-use web-based design interface
- Multicloud support
- Strong data source and client integration, the offering should have wide appeal,
This report from GigaOm, an independent technology research and analysis firm, explores data virtualization products and technologies and how they can help organizations simplify the query process for end users. It analyzes the top data virtualization platforms in the market, weighs the key criteria and evaluation metrics used to assess these solutions, and identifies important technologies to consider for the future.
The GigaOm Radar for Data Virtualization report provides an overview of the leading data virtualization platforms in the market today and recognizes platforms that excel in particular categories. It is relevant to both organizations looking to extend investments in existing platforms as well as to those thinking about adapting a data virtualization solution for their analytics projects.
Download this report to learn more for your data virtualization strategy as well as:
- Key criteria and evaluation metrics comparison
- Vendor insights for the leading data virtualization providers
- GigaOm analysts’ assessment of data virtualization product features and decision criteria
- Why AtScale was identified as an “Outperformer” for data virtualization