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Hasso Plattner on In-Memory Computing, OLAP, and OLTP

by Jacquelyn Howard

June 9, 2010

by Jacquelyn M. Howard, Senior Managing Editor, BI Expert

After hearing the term “in-memory computing" quite a bit at the recent SAPPHIRE conference, I was happy to come across a paper by Hasso Plattner, “A Common Database Approach for OLTP and OLAP Using an In-Memory Column Database.” (For background on in-memory computing, check out Davin Wilfrid’s recent blog, which does a fine job of going over the basics.)

In the paper, Plattner talks about the use of data warehouses as a “compromise,” saying:

The flexibility and speed we gained had to be paid for with the additional management of extracting, and loading data, as well as controlling the redundancy.

In search of a better way to store data, Plattner details a 2 ½ year study of in-memory computing. This study developed after SAP tests with the Hasso Plattner Institute for IT Systems Engineering revealed that column storage took less memory to run than row storage.

I suggest you take a moment to download the whitepaper. In addition to Plattner’s step-by-step analysis of the study’s results, he also offers his view for the future as well as a number of helpful references. I particularly like his vision for meetings in the future in which, as Plattner says:

[All] business transactions [and] queries, including unrestricted aggregations and time-based sequences, can be answered in just a couple of seconds (including the surprisingly costly presentation layer).

Figure source: “A Common Database Approach for OLTP and OLAP Using an In-Memory Column Database

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