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German Edition Early June of “In-Memory Data Management – An Inflection Point for Enterprise Applications”

German Edition Early June of “In-Memory Data Management – An Inflection Point for Enterprise Applications”

First German Version at all will be available in June by Gabler/Springer:

Based on the Demand from German Companies for a German Version for their Employees, the translation of the First Version of the Book was initiated. A Translation is alway a time-consuming process and needed to get high quality.

The German Version will be first published at the In-Memory Conference http://www.in-memory.cc/ early June.

 

 

Preview-Quote for new Book by CEO of leading Online Games Company with around 300 mio Users

Preview-Quote for new Book by CEO of leading Online Games Company with around 300 mio Users

It rarely happens that an emerging new technology can be seen as a “game changer” for a whole industry. But I think this is the case when it comes to in-memory database systems. Tasks which took hours or days can now be executed in seconds which is the technical foundation for establishing completely new business ideas. It dramatically speeds up the execution time of data analytics and thereby creates a much greater experience for the end user on our Bigpoint Gaming Platform. The book “In-Memory Data Management – Technology and Applications” from Hasso Plattner and Alexander Zeier describes not only the technical foundations but also the implications for new exciting applications.

Heiko Hubertz (CEO and Founder, Bigpoint GmbH, Hamburg, Germany / Bigpoint Inc., San Francisco, USA)

Preview-Quote for new In-Memory Book Edition by CIO Allianz, Dr. Schneider

Preview-Quote for new In-Memory Book Edition by CIO Allianz, Dr. Schneider

 


Being IT savvy and leveraging advances in Information Technology is the most important competitive advantage in today’s business world. I see in-memory technology as described in the book In-Memory Data Management – Technology and Applications from Plattner and Zeier as one of the most important innovations in the field of IT. The value for the economy as a whole far outweighs the effort of adapting the applications to this new standard. It dramatically speeds up the execution time of business processes, it allows for significantly more detailed and real-time data analytics and thereby creates a much greater experience for the end user. It brings business computing to a level where it is absolutely snappy and fun to work with.

Dr. Ralf Schneider (CIO Allianz, Munich, Germany)

 

Focus of new extented Book Edition “In-Memory Data Mangement – Technology and Applications”

Focus of new extented Book Edition “In-Memory Data Mangement – Technology and Applications”

 

You can Pre-Order the new Book now at Amazon,  click here !

The new content in the extended Book Edition “In-Memory Data Management” by Hasso Plattner and Alexander Zeier with the new Book Subtitle “Technology and Applications” (to point out the “In-Memory Application Focus” already in the subtitle) targets the development and deployment of data-intensive applications that are designed for leveraging the capabilities of in-memory database systems. Among other new content, we introduces an in-memory application programming model that includes the most important aspects and guidelines for developing in-memory applications. To ease the tasks of application developers and database administrators, we discuss the graphical creation of database views. Finally, we also elaborate on new features on application level  through the combination of data analytics and text search  and by presenting two new industry case studies Charite (HANA Oncolyzer,  new App which combines structured and unstructured Data) and Hilti.

Power of Collaborative Economy – Zipcar CEO

Power of Collaborative Economy – Zipcar CEO

Impressive Keynote at MIT by Zipcar founder and former CEO Robin Chase, Key for Success is using Open Capacity in any Field. Take exzess capacity + plattform: Collaborative Economy – People thrive at the Center . Smartphone have excess capacitiy, too.

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Many Excited Students line up to ask Robin Questions, different than in Germany.

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My Keynote at SAP Univ. Alliance Conference Americas 2012

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?

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.