SAP High-Performance Analytic Appliance Software

SAP AG released technical details of SAP High-Performance Analytic Appliance (SAP HANA) software, announced at SAP TechEd 2010 Bangalore.

The SAP in-memory computing engine that resides at the heart of SAP HANA is an integrated database and calculation layer that allows the processing of massive quantities of real-time data in main memory to provide immediate results from analyses and transactions.

Like any standard database, the SAP in-memory computing engine supports industry standards such as SQL and MDX but also incorporates a high-performance calculation engine that embeds procedural language support directly into the database kernel. This approach eliminates the need to read data from the database, process it and then write data back to the database.

Technical Proof Points
Show Unprecedented Results With Customer Data
The SAP in-memory computing engine delivers technical breakthroughs at the fundamental levels such as CPU core utilization and massively parallel processing across nodes.

Through work with customers during the SAP HANA pilot phase, SAP has been able to demonstrate innovation in three areas:

• Speed: The SAP in-memory computing engine has the ability to scan 2 million records per millisecond per core with over 10 million complex aggregations calculated on the fly per second per core. These results were attained with real customer data running on standard Intel processors. This performance has the potential to transform business processes. For example, as part of a consumer product goods customer proof of concept, SAP has implemented a real-world scenario on SAP HANA that demonstrates the ability to perform arbitrarily complex queries on over 450 billion records in a matter of seconds.
• Scalability: The core engine of SAP HANA has been designed ground-up around a multi-core architecture and implements adaptive, cache-aware algorithms. As a result, performance scales linearly across cores, CPUs and servers. Current analyses indicate full parallelization at 1000 cores and beyond. The implications: a future proof technology that will continue to provide price performance as server core density continues to increase exponentially.
• Compression: Lastly, the SAP in-memory computing engine employs compression algorithms and data structures that minimize the memory footprint required to run the system while still maintaining full support for OLTP workloads. The same 450 billion record system referenced above was implemented on less than three terabytes of physical memory.

In-Memory Computing Engine
and Native In-Memory Applications
to Transform Enterprise Software Industry
SAP has used its understanding of how enterprise applications interact with the database to consolidate parts of the application layer such as business logic and object frameworks. This optimization is reflected in further substantial performance gains. For example, during the SAP HANA pilot phase, SAP has implemented core application scenarios such as Dunning with a 1,200x improvement in performance. Customer application scenarios that currently take over two to three hours now run in less than five seconds.

The SAP in-memory computing engine contains an integrated programming environment that allows the creation, inclusion and extension of native business functions that can be defined in a variety of languages such as SQL scripting, C++ and soon, Project R and Java Script. The SAP in-memory computing engine offers a unified information modeling design environment and can access data from both non-SAP SAP sources. Thus, the optimization and simplification the SAP in-memory computing engine provides does not come at the cost of flexibility.