Complement Warm Data Management in SAP HANA with Dynamic Tiering

  • by Christian Savelli, Senior Manager, COMERIT
  • June 17, 2015
Christian Savelli describes the Dynamic Tiering option available starting with SAP HANA Support Package 9, which enables a more effective multi-temperature data strategy. It offers management of warm data content via the extended table concept, representing a major enhancement from the loading/unloading feature currently available.
Learning Objectives

Reading this article you will learn:

  • How SAP HANA Dynamic Tiering completes the spectrum of multi-temperature data management
  • How to unload tables from SAP HANA main memory using SAP HANA studio
  • Step-by-step extended table configuration for SAP BW providers as well as SAP HANA native tables
Key Concept

The term extended table refers to tables logically defined within one application, but having their contents stored within a secondary application. This setup allows the primary application to save on storage while retaining access to the data as well as control over the metadata of the so-called extended tables. SAP HANA Dynamic Tiering introduces this concept to the SAP HANA application itself, by allowing selected SAP HANA tables to be defined as extended tables. SAP HANA’s main memory storage acts as the primary application while SAP HANA disk storage assumes the role of a secondary application. In other words, SAP HANA extended table contents are solely stored in the SAP HANA disk but are managed and can be accessed like any other regular SAP HANA table, albeit providing slightly slower data retrieval when compared to in-memory content. 

Having data loaded into memory for rapid access and then replicated to disk for durability is the pivotal concept of the SAP HANA in-memory database. However, having all data loaded into memory all the time is not a feasible, cost-effective, or, in many cases, even a desired proposition.

A major contribution to this reality is that the rapid decrease of cost per gigabyte of memory observed in the last decade has been counterbalanced by an even larger, exponential growth of the data to be stored. In other words, more dollars are spent today on memory not because of its unit cost but because many more units of memory are required to store the massive amount of data being generated. However, even within this data avalanche it is important to address the simple fact that not all the data is to be deemed critical and required to be kept in-memory for super-fast access and analysis.

A multi-temperature data strategy is therefore crucial for managing data according to its relevance. It can help at the same time to promote a more effective allocation of SAP HANA memory resources, both RAM and disk based.

Christian Savelli

Chris Savelli, senior manager at COMERIT, has been dedicated to SAP BI and Analytics projects since 1998.  He holds multiple SAP certifications covering HANA, BW and ECC applications and has expertise in managing all aspects of the information creation process, utilizing SAP BI technologies to satisfy strategic, analytical and reporting needs. Chris Savelli started his career at SAP and subsequently held senior level positions at consulting companies Deloitte and Accenture. His education background includes a bachelor of science degree in robotics and a master of science degree in engineering both from the University of Sao Paulo, as well as a post-graduate diploma in business administration from the University of California at Berkeley.

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