Management of multidimensional discrete data
The VLDB Journal — The International Journal on Very Large Data Bases - Spatial Database Systems
Performance Evaluation of Multidimensional Array Storage Techniques in Databases
IDEAS '99 Proceedings of the 1999 International Symposium on Database Engineering & Applications
Index-based multidimensional array queries: safety and equivalence
Proceedings of the twenty-sixth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Efficient Map Portrayal Using a General-Purpose Query Language
DEXA '09 Proceedings of the 20th International Conference on Database and Expert Systems Applications
Putting Pixels in Place: A Storage Layout Language for Scientific Data
ICDMW '10 Proceedings of the 2010 IEEE International Conference on Data Mining Workshops
SciQL, a query language for science applications
Proceedings of the EDBT/ICDT 2011 Workshop on Array Databases
NoDB: efficient query execution on raw data files
SIGMOD '12 Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data
Data vaults: a symbiosis between database technology and scientific file repositories
SSDBM'12 Proceedings of the 24th international conference on Scientific and Statistical Database Management
Breaking the big data barrier by enhancing on-board sensor flexibility
Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data
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Array DBMSs extend the set of supported data structures in databases with (potentially large) multi-dimensional arrays. This information category actually comprises a core data structure in many scientific applications. When it comes to Petabyte archives, storage costs prohibit importing (i.e., copying) such data into a database. Therefore, in-situ processing of database queries is required, that is: evaluating queries on the original files, without previous insertion into the database. We have implemented such an in-situ feature for the rasdaman Array DBMS. In this demonstration, we show with rasdaman how query processing in array databases can simultaneously rely on arrays stored in the database -- as usual -- and in operating system files, like preexisting archives.