Parallel database systems: the future of database processing or a passing fad?
ACM SIGMOD Record - Directions for future database research & development
Transaction Processing: Concepts and Techniques
Transaction Processing: Concepts and Techniques
Knowledge Discovery in Databases: An Attribute-Oriented Approach
VLDB '92 Proceedings of the 18th International Conference on Very Large Data Bases
An Introduction to Database Systems
An Introduction to Database Systems
File System Forensic Analysis
Evaluating Data Handling Performance of ISSEI Data Management Method
Proceedings of the 2009 conference on New Trends in Software Methodologies, Tools and Techniques: Proceedings of the Eighth SoMeT_09
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A new data management method called ISSEI was proposed in the previous report [1], to avoid slowing down of data retrieving time for the database that has an inherent nature of ever growing data volume. ISSEI's data handling performance, namely adding, retrieving, updating and deleting data were evaluated. Through the evaluation, it was confirmed that ISSEI's data handling performances are not dependent on the database size, while the conventional DBMS such as MS SQL Server requires more time for data handling as the database size grows [6].This paper deals with evaluations of ISSEI's performance limitation on system operation and maintenance toward applying ISSEI to a corporate knowledge database that has growing data volume. Through the evaluations, interesting results were obtained. One interesting result is that ISSEI's performance dependency on the data volume size is maintained up to the upper capacity of hard disk. Another interesting result is that data recovery performance of ISSEI is drastically degraded by the length of data records. From the two results, it is concluded whether ISSEI can be applied for the database that has growing data volume or not.