The announcement of the SAP HANA platform has created a lot of buzz in the IT and business world. In the last few months, SAP HANA has seen a great leap forward in its development tools. It is now much simpler to use. Today we have a central platform that remains as solid and stable as before, while the development platform has been significantly improved.
Why HANA?
Now a days enormous data volumes are being generated, doubling in size every two years, primarily on account of increasing electronic data sources. Conventional data sources or graphical representation technologies simply can’t process these volumes. We need new ways to solve this problem, ideas for how to cope with the collection, storage, distribution, search techniques, analysis and graphical representation of such large volumes – in acceptable runtimes. Add to that the fact that part of this data is unstructured.
Until now, BI in companies has been affected by the fact that data is no longer current by the time it’s used for analysis. Analysis takes too long and can’t aid decision-making. In the cocktail of big data issues, real-time technologies no doubt make the most direct contribution to improving corporate BI. Another major drawback with the current BI in companies is the fact that almost the only data being referred to is structured data.
Today’s business users need to react much more quickly to changing customer and market environments. They demand dynamic access to raw data in real time. SAP HANA empowers users with flexible, on-the-fly data modeling functionality by providing no materialized views directly on detailed information. SAP HANA liberates users from the wait time for data model changes and database administration tasks, as well as from the latency required to load the redundant data storage required by traditional databases.
Some use the term “in-memory” in the context of optimizing the I/O access with database management, centering on accessing data from the hard disk by pre-storing frequently accessed data in main memory. The term is also used for a traditional relational database running on in-memory technology. Some solutions offer columnar storage on traditional hard-disk technology, while other platforms offer the option of storing data on solid state disks (SSD). Although these disks have no moving parts and access data much more rapidly than hard disks, they are still slower than in-memory access.
Only SAP HANA takes full advantage of all-new hardware technologies by combining columnar data storage, massively parallel processing (MPP), and in-memory computing by using optimized software design.
Why SAP HANA is a game changer?
Imagine you own a retail store that wants to treat its loyal customers by offering them discounts on their next purchase. A customer just bought something and passed her credit card to the retail executive. Just at the time the retail executive swipes her credit card, the internal system immediately gives him the information that last time she bought black shoes at your store. You instantly offered her a discount on a black dress she might be interested in, that will go well with her black shoes!
This is the power of real-time data analysis and decision making to improve business performances manifolds!. SAP HANA has several incredible features that set it apart from traditional databases. Let’s delve into these and find out why SAP HANA is getting so popular:
1. Columnar Data Storage
2. In-Memory Database System
3. Parallel Processing
4. SAP HANA provides Real-time Analytics
5. Innovations are possible With SAP HANA
What are the technical components that make up HANA?
SAP HANA is a combination of three different products – TREX: a search engine, P*Time: an in-memory, light-weight online transaction relational database management system (OLTP RDBMS) technology and MaxDB: a database technology with persistence, conventional RDBMS features and columnar storage capabilities. SAP built the HANA appliance in collaboration with Stanford University and Hasso Plattner institute in Germany.
The earlier in-memory products of SAP were based on TREX and Live Cache technologies. For e.g., BI Accelerator, BI Explorer, Enterprise Search. SAP SCM-Advanced Planning and Optimization is based on Live Cache.
At the time of launch, HANA started with 1TB of RAM and supported up to 5TB of uncompressed data. By 2011, RAM capacity of 8TB supported up to 40TB of uncompressed data. By 2012, HANA was able to run on servers with 100TB of RAM powered by IBM.
What are the landscape considerations for SAP HANA?
SAP HANA supports ABAP (Advanced Business Application Programming) and doesn’t support Java stack based applications. It works only on SUSE Linux OS and supports distributed installations. Customer’s HANA Appliance has to be installed only on servers provided by SAP certified hardware partners.
If SAP HANA and Hadoop come together?
Hadoop is a free, Java-based programming framework that supports the processing of large data sets in a distributed computing environment. It is part of the Apache project sponsored by the Apache Software Foundation.
Hadoop makes it possible to run applications on systems with thousands of nodes involving thousands of terabytes. Its distributed file system facilitates rapid data transfer rates among nodes and allows the system to continue operating uninterrupted in case of a node failure. This approach lowers the risk of catastrophic system failure, even if a significant number of nodes become inoperative.The Hadoop framework is used by major players including Google, Yahoo and IBM, largely for applications involving search engines and advertising. The preferred operating systems are Windows and Linux but Hadoop can also work with BSD and OS X.
SAP HANA is particularly efficient at making real-time decisions and provides support systems for decision-making. It is also very good at managing large amounts of data, although not yet at the same level as Hadoop.
On the other hand, Hadoop enables large amounts of data to be stored arbitrarily in an efficient way. One of its primary strong points is that it allows us to find a needle in a (huge and unstructured) haystack. In short, it carries out real and complex data mining, always running in batch-processing mode.
After testing both technologies in a pilot development, GFT strongly supports the combination of SAP HANA and HADOOP as complementary technologies. With this joint venture we can face the challenge of managing large volumes of data, both in terms of speed and on a variety of scales. The following chart compares volume and velocity against volume and variety for SAP HANA and Hadoop, as well as the combination of both. Evidently, a combination of the two enables the total spectrum of possibilities to be covered, and therefore produces the optimum results.
In conclusion, combining both technologies can leverage their individual strengths allowing them to build a comprehensive Big Data solution. SAP is currently working on integrating SAP HANA and HADOOP.
Is it a platform?
While the SAP High Performance Analytics Appliance (HANA) initially started out as a specialty engine designed to run analytic applications, HANA has rapidly morphed into a full-blown database platform. In fact, if you include all the database engines that SAP now owns such as Sybase and HANA, the company says it will be the number two supplier of database engines by 2015.
The interesting fact here is, SAP plans to move its current data warehouse offering that runs on top of its NetWeaver middleware to the HANA platform. The company also plans to deliver master data management and data governance services via HANA while also moving a range of business intelligence, predictive analytics, OLAP functionality and enterprise performance management applications to the platform as well.
River Definition Language (RDL):
River Definition Language (RDL), is a new integral language for developing native business applications running on top of SAP HANA. River focuses on intent, using an object-oriented, highly declarative, and modular syntax. It covers all aspects of the application, including error handling and access control. River cross-compiles into efficient code that runs either in XS (Javascript) or in the SAP HANA Database Engine (SQLScript).
Key Design Principles:
- No Runtime
- Simplicity
- Coherency End to End
- Openness
Is it time to switch to SAP HANA?
Now SAP Business Suite customers are wondering whether they should replace their underlying relational databases with this new technology. In-memory databases (IMDBs) have the ability to provide real-time information in nanoseconds instead of milliseconds, a capability that is important for many emerging applications.
So, whether an insurance company wants to calculate the premium amount on various policies or a hospital requires data of all the heart surgeries taken place in the last quarter or a Real estate wants quick access to its database to follow-up with a client, SAP HANA can do all these with the kind of features it is blessed with! Characteristics like no aggregate tables, strong computation power with built-in multitenancy, flexible modelling, large memory footprint, no data duplication and fast data loads leads to immediate access to huge volume of data, in turn leading to quick and efficient decision making.
So, enter the new era of SAP HANA and get started with unbelievable adventures! 
Thanks for your patience