In-Memory Data Management
for Enterprise Applications
High performance in-memory computing will change how enterprises work. Currently, enterprise data is split into two databases for performance reasons. Usually, disk-based row-oriented database systems are used for operational data and column-oriented databases are used for analytics (e.g. “sum of all sales in China grouped by product”). While analytical databases are often kept in-memory, they are often also mixed with disk-based storage media.
Transactional data and analytical data are not stored in the same database: analytical data resides in separate data warehouses, to which it is replicated in batch jobs. As a result, flexible real-time reporting is not possible and leaders are forced to make decisions based on insufficient information in very short time frames.
This is about to change, since hardware architectures have evolved dramatically during the past decade. Multi-core architectures and the availability of large amounts of main memory at low costs are about to set new breakthroughs in the software industry. It has become possible to store data sets of entire Fortune 500 companies in main memory. At the same time, orders of magnitude faster performance than with disk-based systems can be achieved.
Traditional disks are one of the last remaining mechanical devices in a world of silicon and are about to become what tape drives are today: a device only necessary for backup. With in-memory computing and hybrid databases using both row and column-oriented storage where appropriate, transactional and analytical processing can be unified.
In-Memory Key Concepts
Click on the icons below to learn more about the most important building blocks of our in-memory technology:
Combinded column and row store
Minimal Projections
Any attribute as index
Insert only
Bulk load
Multi-core/Parallelization
Active/passive data store
Partioning
Lightweight compression
Dynamic Multi- threading with nodes
Analysis of historical data
SQL Interface on column and rows
No aggregate tables
Single and multi-tenancy
Reduction of Layers
On-the-fly extensibility
Object to relational mapping
Text Retrieval and EXploration
Map Reduce
Group Key
No Disk
Research Topics in Detail | Selected Publications | Videos | Podcasts
Recent news
- In continuation of our commitment over the last seven years, the group of Prof. Hasso Plattner will be present at this years Sapphire in Orlando from May 14 - 16. We will showcase latest research work at our booth no. 2003.
- We are proud to announce our book " A Course in In-Memory Data Management" by Prof. Hasso Plattner. This book is the culmination of six years worth of in-memory research. As such, it provides the technical foundation for combined transactional and analytical workloads inside the same database as well as examples of new applications that are now possible given the availability of the new technology. The book will beavailable at Amazonsoon.
Introductory Poster
Download poster as pdf.
If you are interested in our work, please do not hesitate to get in touch with us at hana-epic (@) hpi.uni-potsdam.de or:
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