Software-as-a-Service applications commonly consolidate multiple businesses into the same database to reduce costs. This practice makes it harder to implement several essential features of enterprise applications. The first is support for master data, which should be shared rather than replicated for each tenant. The second is application modification and extension, which applies both to the database schema and master data it contains. The third is evolution of the schema and master data, which occurs as the application and its extensions are upgraded. These features cannot be easily implemented in a traditional DBMS and, to the extent that they are currently offered at all, they are generally implemented within the application layer. This approach reduces the DBMS to a `dumb data repository' that only stores data rather than managing it. In addition, it complicates development of the application since many DBMS features have to be re-implemented. Instead, a next-generation multi-tenant DBMS should provide explicit support for Extensibility, Data Sharing and Evolution. As these three features are strongly related, they cannot be implemented independently from each other. Therefore, we propose FLEXSCHEME which captures all three aspects in one integrated model. In this paper, we focus on efficient storage mechanisms for this model and present a novel versioning mechanism, called XOR Delta, which is based on XOR encoding and is optimized for main-memory DBMSs.

A multi-tenant database system for Software as a Service (SaaS) should offer schemas that are flexible in that they can be extended different versions of the application and dynamically modified while the system is on-line. This paper presents an experimental comparison of five techniques for implementing flexible schemas for SaaS. In three of these techniques, the database "owns" the schema in that its structure is explicitly defined in DDL. Included here is the commonly-used mapping where each tenant is given their own private tables, which we take as the baseline, and a mapping that employs Sparse Columns in Microsoft SQL Server. These techniques perform well, however they offer only limited support for schema evolution in the presence of existing data. Moreover they do not scale beyond a certain level. In the other two techniques, the application "owns" the schema in that it is mapped into generic structures in the database. Included here are XML in DB2 and Pivot Tables in HBase. These techniques give the application complete control over schema evolution, however they can produce a significant decrease in performance. We conclude that the ideal database for SaaS has not yet been developed and offer some suggestions as to how it should be designed.

In the implementation of hosted business services, multiple tenants are often consolidated into the same database to reduce total cost of ownership. Common practice is to map multiple single-tenant logical schemas in the application to one multi-tenant physical schema in the database. Such mappings are challenging to create because enterprise applications allow tenants to extend the base schema, e.g., for vertical industries or geographic regions. Assuming the workload stays within bounds, the fundamental limitation on scalability for this approach is the number of tables the database can handle. To get good consolidation, certain tables must be shared among tenants and certain tables must be mapped into fixed generic structures such as Universal and Pivot Tables, which can degrade performance.