My Keynote at SAP Univ. Alliance Conference Americas 2012

Alexander Zeier, Visiting Professor, Massachusetts Institute of Technology shared his keynote on “SAP HANA®: In-Memory Data Management for Enterprise Applications” and shared insights about in memory computing to help faculty complement lectures and help students understand this breakthrough technology.

Why In-Memory now?

Imagine you live in a major US city. Now, imagine that every time you want a glass of water, instead of getting it from the kitchen, you need to drive to the airport, get on a plane and fly to Germany and pick up your water there.

From the perspective of a modern CPU, accessing data which is in-memory is like getting water from the kitchen. Accessing a piece of data from the computer’s hard disk is like flying to Germany for your glass of water. In the past the prohibitive cost of main memory has made the flight to Germany necessary. The last few years, however, have seen a dramatic reduction in the cost per megabyte of main memory, finally making the glass of the water in the kitchen a cost effective and much more convenient option.

This orders-of-magnitude difference in access times has profound implications for all enterprise applications. Things that in the past were not even considered because they took so long, now become possible, allowing busi- nesses concrete insight into the workings of their company that previously were the subject of speculation and guess-work.
The in-memory revolution is not simply about putting data into memory and thus being able to work with it “faster”. We also show how the convergence of two other major trends in the IT industry:

a) the advent of multi-core CPUs and the necessity of exploiting this parallelism in software and
b) the stalling access latency for DRAM, requiring software to cleverly balance between CPU and memory activity; have to be harnessed to truly exploit the potential performance benefits.

Another key aspect of in-memory data management, is a change in the way data is stored in the underlying database. This is of particular relevance for the enterprise applications that are our focus. The power of in-memory data management is in connecting all these dots.

The revolutionary Power of an In-Memory Column-Oriented Database 
Our experience has shown us that many enterprise applications work with databases in a similar way. They process large numbers of rows during their execution, but crucially, only a small number of columns in a table might be of interest in a particular query. The columnar storage model allows only the required columns to be read while the rest of the table can be ignored. This is in contrast to the more traditional row-oriented model, where all columns of a table—even those that are not necessary for the result—must be accessed.
The columnar storage model also means that the elements of a given column are stored together. This makes the common enterprise operation of aggregation much faster than in a row-oriented model where the data from a given column is stored in amongst the other data in the row.

Scaling due Parallelization Across Multiple Cores and Machines
Single CPU cores are no longer getting any faster but the number of CPU cores is still expected to double every 18 months. This makes exploiting the parallel processing capabilities of multi-core CPUs of central importance to all future software development. As we saw above, in-memory columnar storage places all the data from a given column together in memory making it easy to assign one or more cores to process a single column. This is called vertical fragmentation.
Tables can also be split into sets of rows and distributed to different processors, in a process called horizontal fragmentation. This is particularly important as data volumes continue to grow and has been used with some success to achieve parallelism in data warehousing applications. Both these methods can be applied, not only across multiple cores in a single machine, but across multiple machines in a cluster or in a data center.

Using Compression for Performance and to Save Space in Main Memory
Data compression techniques exploit redundancy within data and knowledge about the data domain. Compression applies particularly well to columnar storage in an enterprise data management scenario, since all data within a column has the same data type and
in many cases there are few distinct values, for example in a country column or a status column.

In column stores, compression is used for two reasons: to save space and to increase performance. Efficient use of space is of particular importance to in-memory data management because, even though the cost of main memory has dropped considerably, it is still relatively expensive compared to disk. Due to the compression within the columns, the density of information in relation to the space consumed is increased. As a result more relevant information can be loaded for processing at a time thereby increasing performance. Fewer load actions are necessary in comparison to row storage, where even columns of no relevance to the query are loaded without being used.

Summary: Why In-Memory now? 
In-memory data management is not only a technology but a different way of thinking about software development: we must take fundamental hardware factors into account, such as access times to main memory versus disk and the potential parallelism that can be achieved with multi-core CPUs. Taking this new world of hardware into account, we must write software that explicitly makes the best possible use of it. On the positive side for developers of enterprise applications, this lays the technological foundations for a database layer tailored specifically to all these issues. On the negative side, however, the database will not take care of all the issues on its own. Developers must understand the underlying layers of soft- and hardware to best take advantage of the potential for performance gains.

Summary of “In-Memory Data Management – Technology and Applications”

New Book Editition “In-Memory Data Mamangement – Technology and Applications” By Hasso Plattner and Alexander Zeier

In the last fifty years the world has been completely transformed through the use of IT. We have now reached a new inflection point. This book presents, for the first time, how in-memory data management is changing the way businesses are run.

Today, enterprise data is split into separate databases for performance reasons. Analytical data resides in warehouses, synchronized periodically with transactional systems. This separation makes flexible, real-time reporting on current data impossible. Multi-core CPUs, large main memories, cloud computing and powerful mobile devices are serving as the foundation for the transition of enterprises away from this restrictive model.

This book provides the technical foundation for processing combined transactional and analytical operations in the same database, as well as examples of new innovative in-memory applications that run at the speed of thought.

In the year since we published the first edition of this book, the performance gains enabled by the increased use of in-memory technology in enterprise applications has truly marked an inflection point in the market. The new content in this second edition focuses on the development of these in-memory enterprise applications, showing how they leverage the capabilities of in-memory technology.

The book is intended for university students, IT-professionals and IT-managers, but also for senior management who wish to create new business processes by leveraging In-Memory Data Management.

German Innovation Award for In-Memory/HANA

In-Memory/HANA Wins German Innovation Award

SAP and HPI recieved the German Innovation Award (Deutscher Innovationspreis) 2012 in the category of large enterprise for its SAP HANA product.

The jury selected the innovation for its capability of combining three significant technology trends of cloud computing, in-memory computing, and analytics. “With this development, stemming from cooperation between the Hasso-Plattner-Institut, SAP has set a new standard in data processing,” according to the jury.

The German Innovation Award is bestowed each year by the initiative of the same name and backed by corporations Accenture, EnBW, Evonik, and the German business journal Wirtschaftswoche. The jury considers products, innovative business models, processes, and services, as well as organizational and marketing innovations for honors in the categories of large enterprisemidmarket, and startups. This year’s winners were announced am March 16, 2012 in Munich, Germany.

Remarks by Alexander Zeier: 5 Year after starting the In-Memory Work  with Hasso Plattner we  reached the goal.. the next generation of Enterprise Software is here. The Innovation Award was handed over to a respresentative of the HPI  Prof. Meinel, who is the Director of the HPI and also owner of the chair for Security and Internet Systems.


C`t Award New in German:

HANA App Discussion in German: