Big Data

Magic Quadrant for Data Warehouse Database Management Systems

Date Added: Jan 2010
Format: PDF

Today, most data warehouses are mission-critical (see Note 1), serving in an increasingly mixed workload capacity (see Note 2), including as a data source for online applications. "Deep mining" analysts and business analysts are running more ad hoc but equally complex queries and fast-running tactical queries, each with differing service-level expectations. These differing workloads are all competing for CPU, memory and disk access. At the same time, data latency continues to progress from batch to continuous loading demands. In 2009, the latest wave of data warehouse adoption, which includes less mature organizations with little or no data warehouse management experience, continued to grow in size.