Implementation Best Practices for IBM DB2 BLU Acceleration with SAP BW on IBM Power Systems Implementation Best Practices for IBM DB2 BLU Acceleration with SAP BW on IBM Power Systems

Implementation Best Practices for IBM DB2 BLU Acceleration with SAP BW on IBM Power Systems

発行者による作品情報

BLU Acceleration is a new technology that has been developed by IBM® and integrated directly into the IBM DB2® engine. BLU Acceleration is a new storage engine along with integrated run time (directly into the core DB2 engine) to support the storage and analysis of column-organized tables. The BLU Acceleration processing is parallel to the regular, row-based table processing found in the DB2 engine. This is not a bolt-on technology nor is it a separate analytic engine that sits outside of DB2. Much like when IBM added XML data as a first class object within the database along with all the storage and processing enhancements that came with XML, now IBM has added column-organized tables directly into the storage and processing engine of DB2.

This IBM Redbooks® publication shows examples on an IBM Power Systems™ entry server as a starter configuration for small organizations, and build larger configurations with IBM Power Systems larger servers. This publication takes you through how to build a BLU Acceleration solution on IBM POWER® having SAP Landscape integrated to it.

This publication implements SAP NetWeaver Business Warehouse Systems as part of the scenario using another DB2 Feature called Near-Line Storage (NLS), on IBM POWER virtualization features to develop and document best recommendation scenarios.

This publication is targeted towards technical professionals (DBAs, data architects, consultants, technical support staff, and IT specialists) responsible for delivering cost-effective data management solutions to provide the best system configuration for their clients' data analytics on Power Systems.

ジャンル
コンピュータ/インターネット
発売日
2015年
5月11日
言語
EN
英語
ページ数
88
ページ
発行者
IBM Redbooks
販売元
International Business Machines Corp
サイズ
1.4
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