Due to competitive pressures, the demand on companies’ data platforms has grown dramatically to support digital transformation applications that require real-time ingestion of new and existing data, extremely fast response times within large databases and across multiple data stores, and machine-learning insights. The requirement is for a unified analytical data platform with fast multi-thread data loads, a query planner that integrates across data stores, and a fast columnar database with built-in machine learning.

What’s more, location shouldn’t dictate the value of your data. Enabling advanced analytics and in-database machine learning platforms to operate on geographically dispersed data across hybrid cloud environments as if the data were co-located, is becoming a reality that will enable organizations to accelerate time to insight and ultimately business value. This is accomplished while reducing costs associated with data duplication and transfers and increasing the effectiveness of current physical infrastructures.