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Real Time Analytics with SAP Hana

You're reading from   Real Time Analytics with SAP Hana Enhance your SAP HANA skills using this step-by-step guide to creating and reporting data models for real-time analytics

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Product type Paperback
Published in Oct 2015
Publisher
ISBN-13 9781782174110
Length 226 pages
Edition 1st Edition
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Author (1):
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Vinay Singh Vinay Singh
Author Profile Icon Vinay Singh
Vinay Singh
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Toc

Table of Contents (11) Chapters Close

Preface 1. Kickoff – Before We Start FREE CHAPTER 2. SAP HANA Data Modeling Approach 3. Different Ways of SAP HANA Data Load 4. Creating SAP HANA Artifacts Attribute Views and Analytical Views 5. Creating SAP HANA Artifacts – Analytical Privileges and Calculation Views 6. Understanding Text Search and Hierarchies in SAP HANA 7. Using Decision Tables and Transporting SAP HANA Content 8. Consuming SAP HANA Data Models 9. An Introduction to Application Function Library Index

Row and column storage in SAP HANA

Relational databases typically use row-based data storage. SAP HANA uses both (row based and column based data storage)

  • The row storage: This stores records in a sequence of rows
  • The column storage: The column entries are stored in a continuous memory location

Before getting into a SAP HANA specific discussion, let's try to understand how different column storage is from row. The column-oriented database systems (in our case, SAP HANA) perform better than traditional row-oriented database systems on analytical tasks, in areas such as data warehouses, decision support, predictive analysis, and business intelligence applications.

The major reason behind this performance difference in these areas is that column stores are more I/O efficient for read-only queries as they only have to read the attributes accessed by a query from the disk or memory.

Let's see a few factors that optimize performance in the column storage:

  • Compression: The data stored in...
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