Performance and Data Management

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Mensch - Pinpoint Performance Bottlenecks Using ABAP Profiling
Pinpoint Performance Bottlenecks Using ABAP Profiling

by Manfred Mensch | 01/26/2018

In today’s IT landscapes, software developers must not only support the daily operations of modern business, but also balance the performance expectations of end users demanding short response times and IT administrators requiring minimal resource consumption. This article explains how to use transaction SAT (the ABAP Trace tool, also known as Runtime Analysis) to collect the information you need to identify problem areas in your ABAP code and formulate a strategy for optimizing performance.

Performance and Data Management Corner
Sizing Modern SAP HANA Landscapes

by Sebastian Schmitt and Dagmar Kirsamer | 01/31/2017

SAP HANA offers capabilities that are critical for competing in the digital economy, including real-time processing, advanced analytics, and access to insights gleaned from big data and the Internet of Things. To fully benefit from these capabilities in on-premise deployments, you must correctly size the hardware on which the SAP HANA database runs. To help customers with this task, SAP provides an SAP HANA-specific version of its online Quick Sizer tool. This article takes an in-depth look at the SAP HANA version of Quick Sizer and walks through an example of sizing for an on-premise SAP S/4HANA deployment. 

Performance and Data Management Corner
Take SAP Business Warehouse Benchmarking to the Next Level

by Tobias Kutning | 04/26/2016

As a staple of many SAP customer landscapes, SAP Business Warehouse (SAP BW) needs to perform at an optimal level at all times. That is why SAP provides standard application benchmarks to help its customers measure application performance, including SAP BW performance. However, rapid and ongoing changes — such as increasingly complex queries and data transformations in customer workloads — mean that common iterations of SAP BW benchmarks are sometimes no longer applicable to common customer scenarios. Learn how SAP has responded to this need with the SAP BW Advanced Mixed Load (BW-AML) benchmark and how the enhancements in this benchmark can ensure optimized SAP BW performance.

Performance and Data Management Corner
Identifying Performance Problems in ABAP Applications

by Manfred Mensch | 01/14/2016

As IT landscapes become increasingly more complex, it is important to keep business operations running smoothly. Performance issues in ABAP applications, therefore, need to be identified — and rectified — early on for maximum efficiency. Learn how you can leverage the transaction STATS to analyze records, determine bottlenecks, and optimize processes for faster response times, large data throughput, high concurrency, and low hardware cost.

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Benchmarking Modern SAP System Landscapes

by Tobias Kutning | 07/01/2015

Learn how to better support your SAP applications and increase the efficiency of your company’s technological landscape with SAP’s new concurrent benchmark. Concurrent benchmarks show the performance and effectiveness of a shared resource, such as a physical server, storage system, or database, when running multiple SAP applications simultaneously.

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Archiving in the Age of Big Data

by Helmut Stefani | 10/01/2014

Maintaining and updating data in your database can be a huge resource drain, especially considering the rapid growth of data over the last few years. Read this article to see how SAP is helping customers simplify their landscapes while addressing their archiving requirements through SAP Information Lifecycle Management, providing organizations with a less complicated, more efficient alternative for archiving SAP ERP data.

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How to Properly Size an SAP In-Memory Database

by Sebastian Schmitt | 07/01/2014

To fully benefit from SAP HANA, customers must correctly size the hardware required to support the in-memory technique that drives its powerful performance. This article provides an overview of how to properly size for SAP HANA, including an explanation of how sizing for SAP HANA is different from sizing for traditional databases, the different sizing approaches supported by SAP, and how to apply these approaches when sizing for SAP HANA-based implementations.

Best Practices for Achieving High Performance and Scalability in Your System Landscape

by Detlef Thoms | 04/01/2014

Companies are looking to IT for much more than internal back-office services — IT must become a strategic partner of the business, providing innovative solutions in customer and partner interactions as well as product and service development. This article provides guidance in specific areas that are fundamental to performing IT processes optimally, including key performance and scalability indicators, considerations when planning IT landscapes, and best practices for custom development scenarios.

Integrated Retention and Destruction

by John Fiske | 01/01/2014

With expanding compliance requirements, compulsory destruction requirements, and structured and metadata now operating under the same retention regulations as those for unstructured content, today’s enterprise must reconsider methods for information retention. This article explores SAP technology solutions that enable an infrastructure that prevents siloed, disconnected systems and supports managing separate classes of information holistically. Specifically, the article discusses SAP Information Lifecycle Management (SAP ILM) and the SAP Extended Enterprise Content Management (SAP Extended ECM) application by OpenText.

Track Down the Root of Performance Problems with Transaction ST05

Manfred Mensch | 07/01/2013

For companies looking to optimize the performance of their critical applications, being able to identify the sources of performance problems is the key to success. With the Performance Trace (transaction ST05) in the SAP NetWeaver client-server architecture, you can determine the origin of issues in your applications while providing extensive support for examining individual trace records. This article explains how to use ST05 and what to look for when analyzing the results.