Executive Summary
High-scale analytical data platforms are used by organizations to drive better decisions and actions and to provide differentiated products, services, and customer experiences. They provide historical and low-latency data for business intelligence (BI) and analytical analysis, supporting production-scale reporting and dashboarding; ad hoc query and analysis; and, in some cases, a foundation for data science, including machine learning (ML) and artificial intelligence (AI).
The high-scale analytical data platforms market historically has been dominated by database management systems (DBMSs) optimized for analytics and deployed on-premises as the backbone of data warehouses. Today customers are turning to cloud-based database services and emerging options such as data lake query engines and combined lake/warehouse platforms.
This report explores recent trends in analytical data platforms, including the move to cloud DBMS services and the emergence of lake query engines and combined lake/warehouse platforms. Most importantly, it identifies key organizational and technology strategy considerations every company should review before even considering product-specific buying criteria. Technology buyers should use this report as a starting point for an analytical data platform review leading to a short listing of candidates and final proof-of-concept projects.