Multi-tenant SaaS database tenancy patterns


February 2018

Multi-tenant SaaS database tenancy patterns

By: Tree Web Solutions | Tags: database applications, azure cloud, scalability, customizability, multi-tenant software, (SaaS) database

When designing a multi-tenant SaaS application, you must carefully choose the tenancy model that best fits the needs of your application. A tenancy model determines how each tenant’s data is mapped to storage. Your choice of tenancy model impacts application design and management. Switching to a different model later is sometimes costly.

A discussion of alternative tenancy models follows.

A. How to choose the appropriate tenancy model

In general, the tenancy model does not impact the function of an application, but it likely impacts other aspects of the overall solution. The following criteria are used to assess each of the models:

  • Scalability:

    • Number of tenants.
    • Storage per-tenant.
    • Storage in aggregate.
    • Workload.
  • Tenant isolation:  Data isolation and performance (whether one tenant’s workload impacts others).

  • Per-tenant cost:  Database costs.

  • Development complexity:

    • Changes to schema.
    • Changes to queries (required by the pattern).
  • Operational complexity:

    • Monitoring and managing performance.
    • Schema management.
    • Restoring a tenant.
    • Disaster recovery.
  • Customizability:  Ease of supporting schema customizations that are either tenant-specific or tenant class-specific.

The tenancy discussion is focused on the data layer. But consider for a moment the applicationlayer. The application layer is treated as a monolithic entity. If you divide the application into many small components, your choice of tenancy model might change. You could treat some components differently than others regarding both tenancy and the storage technology or platform used.

B. Standalone single-tenant app with single-tenant database

Application level isolation

In this model, the whole application is installed repeatedly, once for each tenant. Each instance of the app is a standalone instance, so it never interacts with any other standalone instance. Each instance of the app has only one tenant, and therefore needs only one database. The tenant has the database all to itself.

Each app instance is installed in a separate Azure resource group. The resource group can belong to a subscription that is owned by either the software vendor or the tenant. In either case, the vendor can manage the software for the tenant. Each application instance is configured to connect to its corresponding database.

Each tenant database is deployed as a standalone database. This model provides the greatest database isolation. But the isolation requires that sufficient resources be allocated to each database to handle its peak loads. Here it matters that elastic pools cannot be used for databases deployed in different resource groups or to different subscriptions. This limitation makes this standalone single-tenant app model the most expensive solution from an overall database cost perspective.

Vendor management

The vendor can access all the databases in all the standalone app instances, even if the app instances are installed in different tenant subscriptions. The access is achieved via SQL connections. This cross-instance access can enable the vendor to centralize schema management and cross-database query for reporting or analytics purposes. If this kind of centralized management is desired, a catalog must be deployed that maps tenant identifiers to database URIs. Azure SQL Database provides a sharding library that is used together with a SQL database to provide a catalog. The sharding library is formally named the Elastic Database Client Library.

C. Multi-tenant app with database-per-tenant

This next pattern uses a multi-tenant application with many databases, all being single-tenant databases. A new database is provisioned for each new tenant. The application tier is scaled upvertically by adding more resources per node. Or the app is scaled out horizontally by adding more nodes. The scaling is based on workload, and is independent of the number or scale of the individual databases.

Customize for a tenant

Like the standalone app pattern, the use of single-tenant databases gives strong tenant isolation. In any app whose model specifies only single-tenant databases, the schema for any one given database can be customized and optimized for its tenant. This customization does not affect other tenants in the app. Perhaps a tenant might need data beyond the basic data fields that all tenants need. Further, the extra data field might need an index.

With database-per-tenant, customizing the schema for one or more individual tenants is straightforward to achieve. The application vendor must design procedures to carefully manage schema customizations at scale.

D. Multi-tenant app with multi-tenant databases

Another available pattern is to store many tenants in a multi-tenant database. The application instance can have any number of multi-tenant databases. The schema of a multi-tenant database must have one or more tenant identifier columns so that the data from any given tenant can be selectively retrieved. Further, the schema might require a few tables or columns that are used by only a subset of tenants. However, static code and reference data is stored only once and is shared by all tenants.

Tenant isolation is sacrificed

Data:  A multi-tenant database necessarily sacrifices tenant isolation. The data of multiple tenants is stored together in one database. During development, ensure that queries never expose data from more than one tenant. SQL Database supports row-level security, which can enforce that data returned from a query be scoped to a single tenant.

Processing:  A multi-tenant database shares compute and storage resources across all its tenants. The database as a whole can be monitored to ensure it is performing acceptably. However, the Azure system has no built-in way to monitor or manage the use of these resources by an individual tenant. Therefore, the multi-tenant database carries an increased risk of encountering noisy neighbors, where the workload of one overactive tenant impacts the performance experience of other tenants in the same database. Additional application-level monitoring could monitor tenant-level performance.

Lower cost

In general, multi-tenant databases have the lowest per-tenant cost. Resource costs for a standalone database are lower than for an equivalently sized elastic pool. In addition, for scenarios where tenants need only limited storage, potentially millions of tenants could be stored in a single database. No elastic pool can contain millions of databases. However, a solution containing 1000 databases per pool, with 1000 pools, could reach the scale of millions at the risk of becoming unwieldy to manage.

Two variations of a multi-tenant database model are discussed in what follows, with the sharded multi-tenant model being the most flexible and scalable.

E. Multi-tenant app with a single multi-tenant database

The simplest multi-tenant database pattern uses a single standalone database to host data for all tenants. As more tenants are added, the database is scaled up with more storage and compute resources. This scale up might be all that is needed, although there is always an ultimate scale limit. However, long before that limit is reached the database becomes unwieldy to manage.


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