Understanding Azure Data Solutions

When building solutions, at some point, you need to be able to read and write data.

There are many kinds of data we may need to consider interacting with when designing and building solutions. Pieces of data aren’t just records in a database – images, documents, and even binary files are all data.

In technical terms, all these different types of data can be grouped into structured, semi-structured, and unstructured data.

Once we have decided what type of data we need to store, we must make choices based on cost, performance, availability, and resilience.

How we plan to use our data can also impact our choice of technology – for example, a web application that simply needs to display images or allow a user to download a document would have very different requirements to a data processing solution that needs to quickly read thousands of small files and output a report.

We must also consider the sensitivity of data...

Technical requirements

This chapter will use the Azure portal (https://portal.azure.com) throughout for the examples.

Understanding Azure storage types

Before we can choose an Azure data solution, we need to understand what our data is. As mentioned previously, data can be grouped into structured, semi-structured, and unstructured data:

Figure 4.1 – Examples of different types of data

Let’s look at them in detail.

Structured data

Structured data is data that has a predefined definition or schema and is managed in a column and row format – that is, rows of data separated into columns.

This type of data is sometimes stored as a comma-separated or other text-based file that conforms to a set format. By this, we mean it should be easy to read the data a row at a time and parse each bit of data or column. So, in the case of a comma-separated file, each row would be one record, and each column would be separated by a comma.

The key feature here is that we should know ahead of time what shape the data is in – that is, each field is in...

Understanding Azure database options

Microsoft has two core database options – Azure SQL, and Azure Cosmos DB – both of which lend themselves to structured or semi-structured data, respectively. Azure SQL has a range of different options. We will consider these first.

Azure SQL

Azure provides three different options for running SQL – a traditional SQL server running on a VM, Azure SQL, and Azure SQL Managed Instance.

The core differences between these three platforms are around how they are managed, and of course how much they cost. Azure SQL on a VM is the most traditional option, and there are specific Azure marketplace images for Windows and Linux that include the cost of the SQL license. If you already have a license, you can still use the marketplace image and apply that license to get a discount, or you can install SQL on a standard VM image.

Azure SQL sits at the opposite end of the Infrastructure-as-a-Service (IaaS) – Platform-as-a-Service...

Summary

In this chapter, we have delved into the various options for storing data in Azure. First, we examined how we need to consider what type of data we are storing – structured, semi-structured, and unstructured data.

We then looked at how we can use and configure Azure storage accounts, before diving into the various SQL options we have available to us.

Finally, we looked at Cosmos DB, a modern, cloud-native, NoSQL database solution that enables us to build truly global solutions.

In the next chapter, we will look at how we might migrate existing applications to Azure. We will consider the options from a compute perspective, as well as how Azure data solutions map to on-premises data storage mechanisms.