Updates to Xcalar 1.2 include user-friendly UI/UX that does not require programing skills to design models, create queries, synthesize schemas, build regression analysis algorithms, and even design new Machine Learning algorithms.
The ability to scale-out to hundreds of nodes, thousands of users, and petabytes of data; point-and-click access to directly read all data types (semi-structured, unstructured, and structured) stored in the cloud or on-prem (Amazon S3, Microsoft Azure Storage, Google Cloud Storage, HDFS, SAN, NAS, NFS, or local file systems); on-prem or in the cloud deployment; seamless integration with leading visualization tools such as Tableau, Microsoft Power BI, Looker, Domo, Qlik, and a variety of reporting tools; and more.
In addition to the platform update, Xcalar also announced it has secured over $21 million in venture funding to date with its Series A round led by Khosla Ventures. Other investors include industry visionaries Andy Bechtolsheim and Diane Greene, and Silicon Valley venture capital firm, Merus Capital.
For more information about this news, visit www.xcalar.com.
