Identify data services

• 5 minutes

Microsoft Azure is a cloud platform that powers the applications and IT infrastructure for some of the world's largest organizations. It includes many services to support cloud solutions, including transactional and analytical data workloads.

Some of the most commonly used cloud services for data are described below.

Azure SQL

Azure SQL is the collective name for a family of relational database solutions based on the Microsoft SQL Server database engine. Specific Azure SQL services include:

• Azure SQL Database – a fully managed platform-as-a-service (PaaS) database hosted in Azure.
• Azure SQL Managed Instance – a hosted instance of SQL Server with automated maintenance, which allows more flexible configuration than Azure SQL DB but with more administrative responsibility for the owner.
• Azure SQL VM – a virtual machine with an installation of SQL Server, allowing maximum configurability with full management responsibility.

Database administrators typically provision and manage Azure SQL database systems to support line of business (LOB) applications that need to store transactional data.

Data engineers may use Azure SQL database systems as sources for data pipelines that perform extract, transform, and load (ETL) operations to ingest the transactional data into an analytical system.

Data analysts may query Azure SQL databases directly to create reports, though in large organizations the data is generally combined with data from other sources in an analytical data store to support enterprise analytics.

Open-source databases in Azure

Azure includes managed services for popular open-source relational database systems, including:

• Azure Database for MySQL - a simple-to-use open-source database management system that is commonly used in Linux, Apache, MySQL, and PHP (LAMP) stack apps.

• Azure Database for MariaDB - a newer database management system, created by the original developers of MySQL. The database engine has since been rewritten and optimized to improve performance. MariaDB offers compatibility with Oracle Database (another popular commercial database management system).

• Azure Database for PostgreSQL - a hybrid relational-object database. You can store data in relational tables, but a PostgreSQL database also enables you to store custom data types, with their own non-relational properties.

As with Azure SQL database systems, open-source relational databases are managed by database administrators to support transactional applications, and provide a data source for data engineers building pipelines for analytical solutions and data analysts creating reports.

Azure Cosmos DB

Azure Cosmos DB is a global-scale non-relational (NoSQL) database system that supports multiple application programming interfaces (APIs), enabling you to store and manage data as JSON documents, key-value pairs, column-families, and graphs.

In some organizations, Cosmos DB instances may be provisioned and managed by a database administrator; though often software developers manage NoSQL data storage as part of the overall application architecture. Data engineers often need to integrate Cosmos DB data sources into enterprise analytical solutions that support modeling and reporting by data analysts.

Azure Storage

Azure Storage is a core Azure service that enables you to store data in:

• Blob containers - scalable, cost-effective storage for binary files.
• File shares - network file shares such as you typically find in corporate networks.
• Tables - key-value storage for applications that need to read and write data values quickly.

Data engineers use Azure Storage to host data lakes - blob storage with a hierarchical namespace that enables files to be organized in folders in a distributed file system.

Azure Data Factory

Azure Data Factory is an Azure service that enables you to define and schedule data pipelines to transfer and transform data. You can integrate your pipelines with other Azure services, enabling you to ingest data from cloud data stores, process the data using cloud-based compute, and persist the results in another data store.

Azure Data Factory is used by data engineers to build extract, transform, and load (ETL) solutions that populate analytical data stores with data from transactional systems across the organization.

Microsoft Fabric

Microsoft Fabric is a unified Software-as-a-Service (SaaS) analytics platform based on an open and governed lakehouse that includes functionality to support:

• Data ingestion and ETL
• Data lakehouse analytics
• Data warehouse analytics
• Data Science and machine learning
• Realtime analytics
• Data visualization
• Data governance and management
• AI-powered insights

Data engineers can use Microsoft Fabric to create a unified data analytics solution that combines data ingestion pipelines, data warehouses, real-time analytics, business intelligence, and AI-powered insights through a single service all centrally stored with Microsoft OneLake.

Azure Databricks

Azure Databricks is an Azure-integrated version of the popular Databricks platform, which combines the Apache Spark data processing platform with SQL database semantics and an integrated management interface to enable large-scale data analytics.

Data engineers can use existing Databricks and Spark skills to create analytical data stores in Azure Databricks.

Data Analysts can use the native notebook support in Azure Databricks to query and visualize data in an easy to use web-based interface.

Azure Stream Analytics

Azure Stream Analytics is a real-time stream processing engine that captures a stream of data from an input, applies a query to extract and manipulate data from the input stream, and writes the results to an output for analysis or further processing.

Data engineers can incorporate Azure Stream Analytics into data analytics architectures that capture streaming data for ingestion into an analytical data store or for real-time visualization.

Azure Data Explorer

Azure Data Explorer is a fully managed, standalone, big data analytics platform that offers high-performance querying of log and telemetry data.

Data analysts can use Azure Data Explorer to query and analyze data that includes a timestamp attribute, such as is typically found in log files and Internet-of-things (IoT) telemetry data.

Microsoft Purview

Microsoft Purview provides a solution for enterprise-wide data governance and discoverability. You can use Microsoft Purview to create a map of your data and track data lineage across multiple data sources and systems, enabling you to find trustworthy data for analysis and reporting.

Data engineers can use Microsoft Purview to enforce data governance across the enterprise and ensure the integrity of data used to support analytical workloads.