Dell PowerEdge R940xa SQream DB on - Page 5

mathematical operations, and joining on any number and types of keys. These functions have been fine-tuned to handle a wide range of complex big data queries, across several industries. These capabilities enable actionable insight and immediate action. The ability to ask any kind of question about a wide variety of information while it is still relevant and valuable distinguishes SQream DB from other solutions, especially when the data produced is in the terabyte to petabyte range. Some of the highlights are: ➢ Enabling and empowering BI analysts and data scientists by treating the root cause of data warehousing problems first. ➢ Companies should have the freedom to decide how much capacity they require, both in storage and in compute. SQream DB detaches the traditional relationship between storage and compute, allowing for independent scaling without affecting the database, and with little to no downtime. ➢ For the highest return-on-investment, a data warehouse should allow any user to query and explore the data at any time, while remaining cost-effective. Traditional data warehouses don't compress data, and force DBAs to prepare cubes, projections, indexes, partitions, distribution keys, and materialized views in order to perform adequately. In contrast, SQream DB's high-throughput architecture and best-in-class compression lets you focus on your data rather than the infrastructure. Just load the data, and it's ready to be queried immediately. No pre-computations necessary. SQream DB's transparent and automatic metadata collection and always-on adaptive GPU compression takes care of the rest, enabling BI analysts and data scientists to query any piece of data immediately. Dell EMC Technical White Paper