SQL Azure : Database Growth-Management Strategies

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When your data is on-premises, you can manage your SQL Server database's growth by adding more storage capacity. Typically, an on-premises storage area network is shared across multiple databases and applications, and it's only a matter of acquiring an extra block of storage from the company's storage-management team. Even though a cost is associated with the storage, you still have control over how you distribute your database growth.

When your data is in SQL Azure, there is a storage constraint of 10GB per database, and you don't have control over how the data files are stored or distributed across the storage area network. Microsoft's argument behind this constraint is that according to the company's analysis, 90% of the SQL Server databases in the world are less than 9GB in size.

With this constraint in mind, how do you architect your database for growth beyond 10GB? The following are a few strategies I have designed for SQL Azure customers:

  • Partition data by location, and distribute it across multiple SQL Azure data centers.

  • Partition data by date into multiple databases.

  • Partition data by business functions into bucket databases.

  • Partition data by tenant, with one configuration and one content database per tenant.

  • Partition data between on-premises and SQL Azure databases.


Because of the SQL Azure size restrictions, all these strategies revolve around creating multiple SQL Server databases in SQL Azure and partitioning data across these databases.

In all the partitioning options, typically a centrally located or replicated configuration database maintains the references and boundary parameters of the content databases. The content databases contain the actual content partitioned by the appropriate boundary condition. These boundary conditions may be one of more of the following: location, date, business function, tenant, and premises. Figure 1 illustrates some of these partitioning strategies.

Figure 1. Partitioning strategies

In Figure 1, the configuration database contains the partition information of the content databases. The application queries the configuration database with query parameters and retrieves the list of content databases that fall within the specified parameters. For example, if your query is for dates in 2007, then the configuration database sends references to the 2007 database. The application can then connect to the appropriate database to execute the query.

Because of the two hops between the application and the databases, there is a performance impact on the data retrieval from the content databases. The configuration database isn't expected to change frequently because it depends on the partitioning parameters, which don't change often. Therefore, you can cache the configuration data in the application and synchronize only when it changes, bypassing an additional hop to the configuration database.

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