Azure SQL is a set of managed, secure, and intelligent SQL Server database solutions that run in the Azure Cloud. MySQL, on the other hand, is a popular Relational Database Management System (RDBMS). When developer productivity and quick time-to-market for innovative solutions is crucial, Azure SQL Database is the appropriate choice for cloud-designed applications. It’s ideal for cloud architects and developers since it minimizes the need to manage the underlying operating system and database with programmatic DBA-like features.
In this article, you will learn more about Azure SQL and MySQL and their key features. You will understand the various methods to set up the Azure SQL MySQL Integration and learn how to migrate your data from MySQL to Azure SQL or vice versa. So, read along to understand how to migrate your MySQL data to the Cloud.
What is Azure SQL?
Azure SQL is a Relational Database that Microsoft offers as a fully managed service. Azure SQL, which is built on top of SQL Server, has a powerful querying layer and rock-solid reliability. It also has AI (Artificial Intelligence)-powered features that make it easier to use.
With 99.99% availability, Azure SQL Database is always running on the most recent stable version of the SQL Server database engine and a patched OS. Azure SQL Database’s PaaS(Platform as a Service) features allow you to focus on the domain-specific database management and optimization tasks that are vital to your business.
For Azure applications and solutions, you can use Azure SQL Database to construct a highly available and high-performance data storage layer. Since it can process both relational data and non-relational formats like graphs, JSON, spatial, and XML, It is a good fit for modern cloud applications. Read Azure SQL Database Simplified 101 to explore how to create and manage Azure SQL Database.
Key Features of Azure SQL
Azure SQL Database is intelligent, scalable, and part of the Azure SQL family. Let’s take a look at some of the remarkable features it offers:
- Scalability: A database in Azure SQL Database can be deployed in 2 ways – Single Database and Elastic Pool. A managed and isolated database is referred to as a Single Database. If you have modern cloud applications and microservices that require a single trustworthy data source, this is a handy tool. A group of Single Databases with a shared set of resources is known as an Elastic Pool.
- Flexible Price Plans: There are several Azure SQL Database Purchasing Models available, including the vCore-based purchasing model, which allows you to choose the number of vCores, memory size, and storage limit; the DTU-based purchasing model, which allows you to compute and manage I/O resources across three service tiers, and the Serverless Model, which allows for automatic resource scaling, such as storage, memory, and speed.
- Advanced Security & Compliance: Azure SQL Database supports various security features, including High-Risk and Medium Risk Users, Unprotected Risky Sign-Ins, Legacy Authentications, and many others.
- Advanced Threat Protection: Azure SQL is a comprehensive package that includes powerful SQL security features. Among the features are database vulnerability management, anomaly detection, and malicious activity detection, all of which might pose a danger to the database’s vital security.
To explore more about Azure SQL, visit the Azure SQL website.
What is MySQL?
MySQL is a SQL-based Relational Database Management System (RDBMS). Tables in the RDBMS are made up of rows and columns, and all data relationships follow a strict logical structure. MySQL is used to build and manage anything from customer-facing web applications to data-driven B2B services. It’s a significant element of most major software stacks. It supports PHP, PERL, JAVA, C++, and C, among other languages.
When compared to Microsoft SQL Server and Oracle Database, MySQL is a faster, more scalable, and easier-to-use Database Management System. It uses a basic Client-Server Model to assist users in managing Relational Databases, or data stored in rows and columns across tables. It makes use of the well-known query language Structured Query Language (SQL), which enables users to conduct all CRUD (Create, Read, Update, and Delete) operations.
Key Features of MySQL
Despite severe competition in the database market today, MySQL is still the database of choice for 5000+ companies, including Uber, Netflix, Pinterest, Amazon, and others. The following are some of the notable features that contribute to MySQL’s success:
- High performance: MySQL enables quick data processing and offers a user-friendly interface. It supports several performance-enhancing features such as Table Index Partitioning and Distinct Memory Caches.
- Scalability: The MySQL platform enables you to smoothly scale up or down your business at any moment. It also works with the most popular operating systems, such as Linux, OS X, and Windows.
- Compatibility: You can take advantage of MySQL’s high-speed and low-latency statistics transactions.
- Robust Transactional Support: ACID (Atomicity, Consistency, Isolation, and Durability) properties are used to ensure that no data is lost or inconsistent.
- Ease of Use: As it uses SQL to query data, anyone with a basic understanding of SQL can quickly do the essential tasks.
To explore more about MySQL, visit the MySQL website.
What are the Methods to Set Up Azure SQL MySQL Integration?
In this section, you will understand how to integrate MySQL and Azure SQL using the following 2 methods:
Method 1: Set Up Azure SQL MySQL Integration using Hevo’s No-Code Data Pipeline
Hevo provides an Automated No Code Data Pipeline that helps you replicate data from MySQL to Azure SQL or Data Warehouses, Business Intelligence Tools, or any other destination of your choice in a completely hassle-free & automated manner.
Hevo’s end-to-end Data Management service automates the process of not only loading data from Azure SQL but also transforming and enriching it into an analysis-ready form when it reaches the destination. Hevo’s Data Mapping feature works continuously to replicate your Azure SQL data to the desired Warehouse and builds a single source of truth for your business.
Check out How to Load Data from MySQL to Any Database in Minutes using Hevo.
Here are more reasons to try Hevo:
- Smooth Schema Management: Hevo takes away the tedious task of schema management & automatically detects the schema of incoming data and maps it to your schema in the desired Data Warehouse.
- Exceptional Data Transformations: Best-in-class & Native Support for Complex Data Transformation at fingertips. Code & No-code Flexibility, designed for everyone.
- Quick Setup: Hevo with its automated features, can be set up in minimal time. Moreover, with its simple and interactive UI, it is extremely easy for new customers to work on and perform operations.
- Built To Scale: As the number of sources and the volume of your data grows, Hevo scales horizontally, handling millions of records per minute with very little latency.
- Live Support: The Hevo team is available round the clock to extend exceptional support to its customers through chat, email, and support calls.
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Method 2: Set Up Azure SQL MySQL Integration using SQL Server Migration Assistant
In this approach, you’ll analyze database objects and data and assess databases for migration using SQL Server Migration Assistant (SSMA) for MySQL.
To successfully set up the Azure SQL MySQL Integration you need to meet the following requirements:
Step 1: Create a New Project in the SSMA
- Open SSMA for MySQL and navigate to File → New Project.
- Enter a name and location for your project in the New Project pane, and then choose Azure SQL Database from the Migrate To drop-down list, as shown below. Select OK.
- Select the Connect to MySQL tab, and then enter the information needed to connect to your MySQL server as shown below.
- Now, right-click on the desired MySQL schema in the MySQL Metadata Explorer window and choose Create Report as shown below. To understand the conversion statistics, problems, and cautions, look over the HTML report.
Step 2: Configure MySQL Azure SQL Data Type Mapping
In this step, you will validate the default data type mappings and, if required, make changes depending on the needs. To do so, follow these steps:
- Navigate to Tools → Project Settings and then select the Type Mappings tab as shown below.
- By choosing the table name in the MySQL Metadata Explorer window, you can alter the type mapping for each table.
Step 3: Connect MySQL to Azure SQL Database
After validating all the data types, follow the steps below to connect your MySQL with Azure SQL database:
- Go to the Connect to Azure SQL Database tab and enter the details in the fields as shown in the image below. Once done, click on Connect as shown below.
- Select the schema you are working on and choose the Convert Schema tab in the upper right corner as shown below.
Review and compare the converted objects to the original objects when to detect any problems and rectify them using the recommendations.
Step 4: Publish & Migrate Azure SQL MySQL Databases
You may begin the migration procedure when you’ve assessed your databases and fixed any inconsistencies. There are 2 phases to migration: publishing the schema and migrating the data.
Publish the Schema:
- Right-click the database in the Azure SQL Database Metadata Explorer window and choose to Synchronize with Database. This action publishes your MySQL schema to the Azure SQL Database.
Migrate the Data:
- Now, right-click the MySQL schema you wish to migrate and then select Migrate Data as shown below.
- View the Data Migration Report once the migration is finished.
- Next, connect to your SQL database with SQL Server Management Studio and validate the data and schema to ensure the migration is successful.
Step 5: Test your Azure SQL MySQL Data Migration
To ensure that everything is functioning smoothly, you should run various tests on your Azure SQL MySQL Integration.
- Develop Validation Tests: Validation queries must be executed against both the source and target databases.
- Set Up a Test Environment: A copy of the source database and the target database should be included in the test environment.
- Run Validation Tests: Validate both the source and the destination, then analyze the results.
- Run Performance Tests: Conduct performance tests on the source and destination, then compare and evaluate the findings.
You can refer to Migration Guide: MySQL to Azure SQL Database for more information.
Limitations of Setting Up Azure SQL MySQL Integration Manually
- You might have observed that Method 2 is quite lengthy and complex. While setting up, you might face some challenges or manual errors can creep into.
- Moreover, you need to manually transform and map your source and target schema. However, in Method 1 you just need to connect your source and target databases, and the schema mapping is handled automatically.
In this article, you read about the features of Azure SQL and MySQL. You also understood the various methods to migrate your data from MySQL to Azure SQL. The first method described an easier alternative to the manual-based approach, by leveraging the Automated Data Pipelines. However, in the second method, you explored the steps to set up Azure SQL MySQL Integration using the SQL Server Migration Assistant (SSMA) for MySQL software.
However, knowing where to start and how to merge data from various applications or databases can be a challenge for many companies. This is where Hevo can help save your day!
Hevo Data is a No-Code Data Pipeline that offers a faster way to move data from 150+ Data Sources including Azure SQL, MySQL, and other 40+ Free Sources, into your Data Warehouse to be visualized in a BI tool. Hevo is fully automated and hence does not require you to code.
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