MySQL has become a popular relational database management system that maximizes the number of transactions per second. When it comes to swiftly entering individual records like customer details, accounts, purchases, bookings, etc, MySQL is the way to go. Though, owing to its Online Transaction Processing(OLTP) architecture, performing computationally complex queries for ad-hoc reporting is time-consuming.
A Data Warehouse like Azure Synapse Analytics can solve this by quickly executing your queries as it stores data by columns rather than rows. Also, replicating data from MySQL to Azure allows you to create a complete customer profile. You can deep dive into the customer journey with sales, marketing, product, and finance data all pooled in together from multiple sources.
You can simply replicate data from MySQL to Azure using the Azure Data Factory that facilitates the data movement via its Copy Data Tool. In this article, you will learn how to effectively move data from MySQL to Azure using this approach.
Note that currently, Hevo doesn’t support Azure as a Destination.
Table of Contents
How to Connect MySQL to Azure?
To get started with the Copy Data Tool’s MySQL to Azure connector, follow the simple steps given below:
- Step 1: Log in to your Azure account and navigate to the Azure Data Factory Overview page. Click on the Copy Data Tool option.
- Step 2: Enter a unique name of your Data Pipeline for the MySQL to Azure data transfer. Once done, click on the Next button.
- Step 3: In this MySQL to Azure Integration step, type MySQL in the search bar and click on the MySQL icon.
- Step 4: A new dialog box will appear on your screen where you can provide your MySQL credentials to allow Azure Data Factory to connect to MySQL. After that, select the tables you want to replicate and move towards the destination step.
- Step 5: Similarly for the destination, search Azure Synapse and click on the respective icon.
- Step 6: Enter your Azure Synapse credentials to complete the connection.
- Step 7: Now, select the table schema mapping and click on the Next button. In this example, the existing table schema is chosen.
- Step 8: Finally, you can now link your account for staging and click on the Next button to start the data replication process.
Azure Data Factory’s Copy Data Tool is effective for the following use cases:
- One Time Migration: Although Azure’s consumption-based pricing is attractive, a long-term data pipeline integration service can be expensive. Hence, it is great for short-term & one-time MySQL to Azure data replication.
- Analysis Ready Raw Data: Since the Copy Data Tool has minimal data transformation capabilities, it isn’t advised to use it on clean, analysis-ready data.
- Azure-based Integrations: Standalone Azure Data Factory would not be sufficient when you need to integrate with data sources outside the Azure Environment. Thus, due to its limited integrations, it is a good option for connecting to Azure-based data sources only.
However, for a multi-cloud strategy, you can’t depend on Azure Data Factory. As it has a limited number of integrations outside the Azure ecosystem, you would need to spend a portion of your engineering bandwidth. Your data engineers would need to design, develop & maintain the ever-changing data connectors while ensuring minimum downtime.
Secondly, data coming in from multiple sources is in different formats. To get to the part where you start your analysis, you need to formulate custom data transformations for filtering, cleaning & standardizing your data. As your data exponentially grows with your scaling business, all of this becomes a heavily time-consuming and resource-intensive task.
A more effortless solution is opting for a No-Code solution that completely manages and maintains the data pipelines for you. Choosing a cloud-based Tool like Hevo allows you to completely focus on your business analysis without worrying about the data transfer process.
You can simply perform complex data transformations on the fly and quickly set up the data pipeline in a matter of minutes without any need for prior technical knowledge.
Summing It All Together
In this article, you have learned how to effectively replicate data from MySQL to Azure using Azure Data Factory. The Copy Data Tool allows you to simply connect to your source & destination with the right credentials and gets your pipeline started right away. This method is a good choice if you rarely need to copy data and require little to no data transformations. Though, when you need to frequently replicate data from multiple sources with complex transformations for complete business analysis, then Hevo is the right choice for you!Visit our Website to Explore Hevo
Hevo provides a beginner-friendly UI that allows a data engineer or a non-technical user such as a business analyst to simply click and set up the data pipeline in a matter of minutes. With 150+ plug and play connectors, you can replicate data from sources like MySQL, and MySQL on Azure Database to a Data Warehouse like Redshift, BigQuery, Snowflake, or a destination of your choice. Currently, Hevo doesn’t support Azure as a destination.
Cleaning, standardizing & preparing your data in the initial stage just takes a few minutes with Hevo’s pre-load data transformations via a simple drag n drop interface or your custom python scripts. No need to go to your data warehouse for post-load transformations. From the comfort of Hevo’s interface, you can simply run complex SQL transformations and get your data in the final analysis-ready form. As Hevo completely manages & maintains your pipelines with zero data loss, you can truly focus on your core business objectives.
Share your experience of connecting MySQL to Azure! Let us know in the comments section below!