A Dynamic Data Storage Architecture for SaaS

In the implementation of Software as a Service (SaaS), Universal Table and Column Store have become the two most typical data storage architecture. However, they both have obvious drawbacks. Microsoft proposed the schema based on Basic-Table combined with Extension-Table (BT & ET) ,in which some of the tenants´ common fields are stored into the basic table to improve the processing efficiency. But the structure of the basic table is irreversible for it´s defined by the service provider in their development stage. Thus none of the extension fields can be stored into the basic table, even if they are accessed much more frequently than the common columns they still need tuple reconstruction. In the paper we improve the BT & ET schema and based on the improved schema we propose a dynamic self-adaptive algorithm. Based on the tenants´ constantly need on data access, we can store some tenant´s frequently accessed extension fields into the basic table by our algorithm.