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think about also upgrading it to support multitenant scenarios. If you have several copies of your database, one for each customer that uses the system, now would be a good time to add the support needed to run those different customers on one database, but still in an isolated manner. If you re building a new system that doesn t need sophisticated transactions, or a complex authorization model, then using Azure Tables is probably best. People tend to fall into two groups when they think of Tables. They re either from ye olde country and think of Tables as a simple data-storage facility that ll only be used for large lookup tables and flat data, or they re able to see the amazing power that a flexible schema model and distributed scale can give them. Looking at Tables without the old blinders on is challenging. We ve been beaten over the head with relational databases for decades, and it s hard to consider something that deviates from that expected model. The Windows Azure platform does a good job of providing a platform that we re familiar and comfortable with, while at the same time giving us access to the new paradigms that make the cloud so compelling and powerful. The final consideration is cost. You can store a lot of data in Azure Tables for a lot less money than you can in SQL Azure. SQL Azure gives you a lot more features to use (joins, relationships, and so on), but it does cost more.
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SQL Azure is a powerful data platform that s familiar to us. It just happens to be run-
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ning in the cloud. This makes it easier to move an application to the cloud, or to build something new, using paradigms and tools that we know and love. We looked at how to create and manage a database in the cloud. The processes and approaches are eerily similar to what you would do when working with a local database, which makes it easy to adopt SQL Azure for your application. There are some limitations because of the virtual nature of the SQL Server, and because the database is running in a shared environment. The sophisticated data engine that is SQL Azure isn t the last stop for SQL in the cloud it s just the beginning. The tools will be upgraded for full support, and the rest of the SQL family will move into the cloud over time. Although the firewall and other security features make it easier to trust putting your data in the cloud, you still need to think critically about whether it s the right place for your data, or whether a blended approach is best for your scenario. Now that you ve moved your data to the cloud, it s time to learn more about how best to query and use data in a cloud application. 14 will look at this from several different angles.
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This chapter covers
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Working with static data Working with dynamic data Working with infrequently changing data
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In previous chapters, we ve shown you what you can do with the Table service, SQL Azure, and caching. In this chapter, we ll look at how you can choose when to use these three technologies. Rather than focusing specifically on the technologies, we ll look at the types of data you can store with each of the technologies and at how each technology will help you store different types of data. We ll look at three types of data in particular: static data, dynamic data, and infrequently changing data. We ll also focus on where you can store the data and how you can efficiently retrieve it. We ll start with static data.
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