Home > Workload Solutions > SAP > Guides > SAP HANA TDI Guides > Dell Validated Design for SAP HANA TDI with PowerEdge Systems > Memory requirements
Dell Technologies recommends that SAP HANA solutions have a homogenous, symmetrical assembly of DIMMs and maximum utilization of all memory channels per processor. The following requirements therefore apply to Intel Xeon Scalable Processors:
The following figures show the optimal DIMM size and count for the possible memory permutations:
*Supported with Intel® Xeon® 4th Generation Scalable Processors only.
Note: When selecting a DIMM size, consider future memory upgrade requirements to avoid having to replace existing DIMMs later. Data management with SAP HANA
The exponential growth of data has increased the demand for scaled-up storage and processing power to keep up with the complexities of enterprise information management. Businesses thirst for a data management strategy that meets their needs for SAP HANA performance and data accessibility with a limited IT budget, while lowering their TCO.
Mission-critical (or “hot”) data is stored in memory on the SAP HANA database for
real-time processing and analytics. Less frequently accessed (or “warm”) data is saved in a lower-cost storage tier while still being managed as a unified part of the SAP HANA database. Retaining and managing older data in this cost-effective way is key in maintaining data growth while minimizing the expense of hardware growth.
Native Storage Extension (NSE) is a native feature of SAP HANA that serves as a warm data solution. NSE boosts the cost-to-performance ratio in a manner comparable to other SAP HANA warm data solutions, such as SAP HANA Extensions Node and SAP HANA Dynamic Tiering. The following figure compares standard SAP HANA in-memory storage with NSE storage:
The capacity of a standard SAP HANA database is limited to the amount of main memory. With SAP HANA NSE, customers can bypass the limit by storing warm data on a storage system. In paging operations, a relatively small SAP HANA memory amount is required for the NSE buffer cache because the cache can manage up to eight times the size of warm data on disk. For example, a 2 TB SAP HANA system without NSE equates to a
1 TB database in memory. By using NSE and adding a 500 GB buffer cache, you can expand your 1 TB database to a 5 TB database consisting of 1 TB of hot data, 4 TB of warm data, and a 500 GB buffer cache to page data between memory and disk.
Note: Only SAP HANA scale-up systems are currently supported with NSE.
Hot (or “column-loadable”) data resides completely in memory for fast processing and is loaded into SAP HANA memory from disk in columns. SAP HANA NSE allows you to designate specific warm data as “page loadable,” and this data is loaded into memory page by page as required for query processing. It is not necessary for page-loadable data to reside completely in memory.
NSE reduces the memory footprint for page-loadable data. The database is partly in-memory and partly on disk, as illustrated in the following figure:
For more information about SAP HANA NSE, see the following documentation: