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October 27, 2017

HPE – SAP HANA Solutions

Revolutionise the Way You Run Your Business

SAP has introduced a new class of solutions that powers the next generation of business applications. The SAP HANA® database is an in-memory database that combines transactional data processing, analytical data processing, and application logic processing functionality in memory. SAP HANA removes the limits of traditional database architecture that have severely constrained how business applications can be developed to support real-time business.

SAP HANA introduces a different way of thinking from both the technical side of how to construct applications and the business side of how to exploit the new functionality. SAP offers an incremental road map that enables your organization to safely explore the technology today, seize opportunities in side byside scenarios, and get prepared for the increasing rate of doing business

Current Generation of Enterprise Solutions

The architectures of current-generation business systems reflect the technological conditions during the long evolution of business solutions:
• Database layer: Database management systems were
designed for optimizing performance on hardware with limited
main memory and with the slow disk I/O as the main
bottleneck. The focus was on optimizing disk access, for
example, by minimizing the number of disk pages to be read
into main memory when processing a query.
• Business application layer: Business software was built with
a sequential processing paradigm. Data tables for the current
scenario were fetched from the database, processed
on a row-by-row basis, and pushed back to the database

 

Technological Transition

Computer architecture has changed. Today’s multicore, multiCPU server provides fast communication between processor cores via main memory or shared cache. Main memory is no longer a limited resource. In 2012 servers with more than 2 terabytes of RAM are available. Modern computer architectures create new possibilities but also new challenges. With all relevant data in memory, disk access is no longer a limiting factor for performance. In 2012 server processors have up to 80 cores, and 128 cores will come in the near future. With the increasing number of cores, CPUs will be able to process more and more data per time interval. That means the performance bottleneck is now between the CPU cache and main memory (see Figure 2). An optimized database technology should focus on optimizing memory access by the processing cores. Simple disk access optimization by caching data in memory may not yield breakthrough performances. To provide an idea about sizes and access speeds of a current memory hierarchy, the table below compares the different layers in this memory hierarchy (CPU characteristics for Intel’s Nehalem architecture).

 As illustrated in Figure 2, the performance bottleneck is between the main memory and the CPU. Simple memory-resident caching with a traditional database system is not the solution. The CPU spends half of the execution time in wasted stalls for two reasons: waiting for data being loaded from main memory into the CPU cache, and the fact that sequential processing of the business application cannot properly utilize the increasing number of processing cores.

SAP HANA Platform Overview

Taking a New Approach to Business Data
Processing

The SAP HANA platform implements a new approach to business data processing. In fact, it is much more than the traditional definition of a database. And the in-memory attribute is much more than a naïve caching of disk data structures in the main memory. A conceptual view of SAP HANA is illustrated in Figure 4. While many of the concepts discussed below may be known in the industry, the specific synergy of SAP HANA, which leverages SAP expertise in different domains, creates a new class of solutions

SAP HANA Benefits for Business Applications

In financial applications, different kinds of totals and balances are typically persisted as materialized aggregates for the different ledgers: general ledger, accounts payable, accounts receivable, cash ledger, material ledger, and so on. With an inmemory column store, these materialized aggregates can be eliminated as all totals and balances can be computed on the fly with high performance from accounting document items.

Eliminating materialized aggregates has several advantages:
• Simplified data model: With materialized aggregates, additional
tables are needed, which make the data model more
complex. In the financials data model for the SAP Business
ByDesign™ solution, for example, persisted totals and balances
are stored with a star schema. Specific business
objects are introduced for totals and balances, each of which
is persisted with one fact table and several dimension tables.
With SAP HANA, all these tables can be removed if totals and
balances are computed on the fly. A simplified data model
makes development more efficient, removes sources of programming
errors, and increases maintainability.
• Simplified application logic: The application either needs to
update the aggregated value after an aggregated item was
added, deleted, or modified, or special aggregation runs
need to be scheduled that update the aggregated values at
certain time intervals, such as once a day. By eliminating persisted
aggregates, this additional logic is no longer required.
• Higher level of concurrency: With materialized aggregates, a
write lock needs to be acquired after each write operation for
updating the aggregate. This limits concurrency and may
lead to performance issues. Without materialized aggregates,
only the document items are written. This can be done
concurrently without any locking.
• “Up-to-datedness” of aggregated values: With on-the-fly
aggregation, the aggregate values are always up-to-date,
while materialized aggregates are sometimes updated only
at scheduled times.

 

 

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