A comparison of the impact of data vault and dimensional modelling on data warehouse performance and maintenance
Abstract
This study compares the impact of dimensional modelling and data vault modelling on the
performance and maintenance effort of data warehouses. Dimensional modelling is a data
warehouse modelling technique pioneered by Ralph Kimball in the 1980s that is much more
effective at querying large volumes of data in relational databases than third normal form data
models. Data vault modelling is a relatively new modelling technique for data warehouses that,
according to its creator Dan Linstedt, was created in order to address the weaknesses of
dimensional modelling. To date, no scientific comparison between the two modelling techniques
have been conducted.
A scientific comparison was achieved in this study, through the implementation of several
experiments. The experiments compared the data warehouse implementations based on
dimensional modelling techniques with data warehouse implementations based on data vault
modelling techniques in terms of load performance, query performance, storage requirements,
and flexibility to business requirements changes.
An analysis of the results of each of the experiments indicated that the data vault model
outperformed the dimensional model in terms of load performance and flexibility. However, the
dimensional model required less storage space than the data vault model. With regards to
query performance, no statistically significant differences existed between the two modelling
techniques.
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