Document databases handle multi-tenancy by providing a structured way to manage data for multiple clients within the same database environment. Multi-tenancy means that a single instance of a software application serves multiple customers, or "tenants," while keeping their data isolated and secure. Document databases achieve this primarily through the use of separate collections, shared collections with tenant identifiers, and access control mechanisms.
One common approach is to create separate collections for each tenant. In this model, each customer has its own collection, ensuring that their data is completely isolated from that of other tenants. For example, if you have tenants A, B, and C, you would create three collections—tenantA_data, tenantB_data, and tenantC_data. This method simplifies security and data management, as applications can query the specific collection for each tenant without worrying about data from other tenants. However, this can lead to increased overhead when scaling, as the number of collections can grow significantly with the addition of new tenants.
Another strategy is to use a single shared collection with tenant identifiers. Here, all tenant data resides in a single collection, and each document includes a field identifying the tenant it belongs to. During queries, the application would use this tenant ID to filter results. For instance, documents might look like { tenantId: "A", data: { ... } }. This approach is more efficient in terms of resource usage and scaling, as it reduces the number of collections. However, it requires careful implementation of access controls to ensure that tenants cannot access each other’s data. Developers need to implement strict query mechanisms and security rules to ensure that only the relevant tenant can see their documents. This balances resource utilization with data privacy and security concerns.