Azure Data Fundamentals
Azure Storage
Cosmos DB
4m 36s
Start course

Microsoft Azure offers services for a wide variety of data-related needs, including ones you would expect like file storage and relational databases, but also more specialized services, such as for text searching and time-series data. In this course, you will learn which services to choose when implementing a data infrastructure on Azure. Two services that are especially important are Azure SQL Database and Azure Cosmos DB.

Learning Objectives

  • Identify the most appropriate Azure services for various data-related needs

Intended Audience

  • People who want to learn Azure fundamentals


  • General knowledge of IT architecture, especially databases


I hope you enjoyed learning about Azure’s data services. Let’s do a quick review of what you learned.

Azure Storage has 4 different redundancy options. Locally-redundant storage is replicated across racks in the same data center. Zone-redundant storage is replicated across three zones within one region. Geo-redundant storage is replicated across two regions. Read-access geo-redundant storage is the same as geo-redundant storage except that if there’s a disaster in your primary region, then you can read your data from the secondary region immediately.

Azure Storage supports five types of data: blobs, files, queues, tables, and disks. Blob storage holds data objects. You can choose from three storage tiers. Hot storage is for data that gets accessed frequently. Cool storage is for data that doesn’t get accessed more than once every 30 days and that needs to be retrieved immediately when requested. Archive storage is for data that doesn’t get accessed more than once every 180 days and that can take up to 15 hours to access when you do need it.

File storage is SMB-compliant, so you can use it as a file share. Queue storage is for passing messages between applications. Table storage is a very simple and inexpensive NoSQL datastore. Disk storage is for the disks that are attached to virtual machines.

StorSimple is a virtual array that you install at your own site. It moves your infrequently used data to the cloud and lets you access that data seamlessly when you need it.

Azure Data Catalog is an index to all of an organization’s data. Each data source has to be manually registered in the catalog.

Azure SQL Data Warehouse is a repository for structured, relational data. It’s used primarily for business reporting and it works with the SQL Server ecosystem.

Azure Data Lake Analytics lets you run U-SQL queries on Azure Data Lake Storage. You can also run queries on Data Lake Storage using Hadoop. The easiest way to run Hadoop is with the HDInsight service.

With Azure Data Factory, you can create data processing pipelines. This lets you automate data movement and transformation.

Azure Analysis Services lets you create data models to make sense of existing data. It sits between databases and business intelligence clients, such as Power BI.

Azure Database for MySQL and Azure Database for PostgreSQL are managed services that provide high availability, backups, security, and compliance for MySQL and PostgreSQL.

SQL Server Stretch Database migrates cold table rows to Azure, but still lets you query them. This saves you money and helps your backups run faster.

Azure SQL Database is the preferred option for moving from SQL Server to Azure, but it’s not 100% compatible with SQL Server, so there may be some reengineering required. 

Azure Table storage is a key/attribute store. It’s schemaless and it automatically creates a primary index. Azure Redis Cache is a simple key/value store. It runs in memory, which is why it’s used as a cache. Azure Data Lake Storage is a NoSQL repository for all kinds of data. Azure Search creates an index of text data so your users can run searches. Time Series Insights collects time-stamped data, such as data from IoT devices, and lets you run queries on it.

Cosmos DB is globally distributed and it provides SLAs for latency, throughput, consistency, and availability.

It has APIs to support various data models, including Table storage, MongoDB, SQL, Graph, and Cassandra.

Now you know how to identify the most appropriate Azure services for various data-related needs.

To learn more about Azure’s data services, you can read Microsoft’s documentation. Also watch for new Microsoft Azure courses on Cloud Academy, because we’re always publishing new courses. Please give this course a rating, and if you have any questions or comments, please let us know. Thanks and keep on learning!

About the Author
Guy Hummel
Azure and Google Cloud Content Lead
Learning Paths

Guy launched his first training website in 1995 and he's been helping people learn IT technologies ever since. He has been a sysadmin, instructor, sales engineer, IT manager, and entrepreneur. In his most recent venture, he founded and led a cloud-based training infrastructure company that provided virtual labs for some of the largest software vendors in the world. Guy’s passion is making complex technology easy to understand. His activities outside of work have included riding an elephant and skydiving (although not at the same time).

Covered Topics