Greenplum is a fast, flexible, software-only analytics data processing engine that has the tools and features needed to make extensive use of any number of hardware or virtual environments that can be used for cluster deployment. One of those features discussed here is the use of file spaces to match data load and query activity with the underlying I/O volumes to support it. Once a physical file space is created across the cluster, it is mapped to a logical tablespace, which is then used during the table and index creation process.
Greenplum Database is built for advanced Data Warehouse and Analytic workloads at scale. Whether the data set is five terabytes on a handful of servers, or over a petabyte in size on a hundred-plus nodes, the architecture of Greenplum allows it to easily grow to meet the data management and concurrent user access requirements of the platform. To manage very large tables, easily measured in billions of rows organized in logical partitions, Open Source Greenplum provides a number of table types and compression options that the architect can employ to store data in the most efficient way possible. Read More