SAS® SCALABLE PERFORMANCE DATA SERVER

Fast, on-demand delivery of data subsets gathered from large enterprise data stores.

Get consistent performance from your reporting and analytic applications. And be confident that your data integration processes will not exceed the available time window, even as your enterprise data volume continues to grow.

Faster subset information gathering

Uses parallel storage technologies and hardware to reduce overhead such as the two-phase commit that's incurred with transactional systems.

Optimized reporting & analytic performance

Separates transactional data stores from reporting and analytic application data stores, enabling you to tune each for the appropriate task requirements.

Faster data integration processing times, regardless of size

Moves data from transactional systems to via an ETL process that uses parallel storage and efficient indexing. Integrated metadata ensures data consistency and reduces time spent maintaining large quantities of data.

Partitioning and parallel processing

Speeds the processing of large amounts of data by partitioning the data across multiple disks and I/O channels.

Unique indexing technology

Uses a hybrid indexing scheme that combines the best features of B-tree and bitmap indexes, reducing storage and accelerating queries.

Query optimization

Improves performance for the types of queries most often found in reporting and analytics applications. Provides star schema optimization and parallel and optimized join methods for data models other than star schemas.

SQL pass-through support

Provides a pass-through facility that enables you to send SQL statements specific to SAS Scalable Performance Data Server directly to the server for execution.

Management and security

Enables administrators to control read, write and modification access to tables, rows, columns and cells on a per-user or per-group basis. Audit logs enable compliance with regulatory obligations.

Support for Hadoop distributions

Provides support for Hadoop distributions (Hortonworks, MapR and Cloudera).

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