“One size fits all” database architectures do not work for DSS
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
Weaving Relations for Cache Performance
Proceedings of the 27th International Conference on Very Large Data Bases
A survey of approaches to automatic schema matching
The VLDB Journal — The International Journal on Very Large Data Bases
SOSP '03 Proceedings of the nineteenth ACM symposium on Operating systems principles
The VLDB Journal — The International Journal on Very Large Data Bases
A relational approach to the capture of DICOM files for Grid-enabled medical imaging databases
Proceedings of the 2004 ACM symposium on Applied computing
C-store: a column-oriented DBMS
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Parallel querying of ROLAP cubes in the presence of hierarchies
Proceedings of the 8th ACM international workshop on Data warehousing and OLAP
Bigtable: A Distributed Storage System for Structured Data
ACM Transactions on Computer Systems (TOCS)
Column-stores vs. row-stores: how different are they really?
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Pig latin: a not-so-foreign language for data processing
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Hive: a warehousing solution over a map-reduce framework
Proceedings of the VLDB Endowment
Xbase: cloud-enabled information appliance for healthcare
Proceedings of the 13th International Conference on Extending Database Technology
HYRISE: a main memory hybrid storage engine
Proceedings of the VLDB Endowment
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Medical data management becomes a real exigency. The emergence of new medical imaging techniques and the necessity to access medical information at any time have led to an inevitable need to find new advanced solutions for managing these critical data. Actual local archiving systems are very expensive and cannot support this heterogeneous and enormous data size. Cloud computing has attracted significant attention due to its major characteristics of elasticity, availability and pay-per-use. A good exploitation of this infrastructure constitutes an effective and promising solution for managing medical data and images. In this position paper, we highlight the challenges in integrating highly heterogeneous data such as DICOM files in the clouds. We then propose a novel hybrid row-column, two-level database architecture for the storage of heterogeneous data over the cloud.