Instead of insisting on a single schema, it is sometimes easier to modify even an existing application to use multiple schemas, as are supported by most relational databases. In this model, the application computes which OU the logged-in user belongs to, and then connects to the appropriate database schema. Such architecture is



FIGURE: Multi-tenancy using multiple schemas

In the multiple schema approach, a separate database schema is maintained for each customer, so each schema can implement customer-specific customizations directly. Meta-data describing customizations to the core schema is also maintained in a separate table, but unlike the Custom Fields table of Figure, this is pure meta-data and does not contain field values in individual records. As a result, the application design is simpler, and in case a legacy application needs to be re-engineered for multi-tenancy, it is likely that the modifications will be fewer and easier to accomplish.

Consider implementing the Edit Customer screen as discussed earlier using a multiple schema approach: The application renders the appropriate fields on the screen using information from the Meta-Data table. When making a database query, the application sets the database schema before issuing data manipulation (i.e. SQL) statements so as to access the appropriate schema.

We have described a rather simple implementation to illustrate the concept of using multiple schemas for multi-tenancy. In practice, web application servers need to have schema names configured during deployment so that they can maintain database connection pools to each schema. Therefore, another level of indirection is usually required, where the customer name (i.e. OU) is mapped to the actual schema name, so that customers can be added or deleted online without bringing the system down.

In the case of a multi-entity scenario within a single organization, the number of users was relatively small, probably in the thousands at most. For a SaaS application, the number of users will be orders of magnitude larger. Thus additional factors need to be considered for a multi-tenant SaaS deployment, such as how many applications server and database instances are needed, and how a large set of users are efficiently and dynamically mapped to OUs so as to be connected to the appropriate application server and database instance.