How to Migrate Data from MySQL to Snowflake Destination?

Unlock the full potential of your MySQL data by integrating it seamlessly with Snowflake. With Hevo’s automated pipeline, get data flowing effortlessly—watch our 1-minute demo below to see it in action!

Relational databases, such as MySQL, have traditionally helped enterprises manage and analyze massive volumes of data effectively. However, as scalability, real-time analytics, and seamless data integration become increasingly important, contemporary data systems like Snowflake have become strong substitutes. After experimenting with a few different approaches and learning from my failures, I’m excited to share my tried-and-true techniques for moving data from MySQL to Snowflake.

In this blog, I’ll walk you through two simple migration techniques: manual and automated. I will also share the factors to consider while choosing the right approach. Select the approach that best meets your needs, and let’s get going!

What is MySQL?

MySQL is an open-source relational database management system (RDBMS) that allows users to access and manipulate databases using Structured Query Language (SQL). Created in the middle of the 1990s, MySQL’s stability, dependability, and user-friendliness have made it one of the most widely used databases worldwide. Its structured storage feature makes it ideal for organizations that require high-level data integrity, consistency, and reliability. Some significant organizations that use MySQL include Amazon, Uber, Airbnb, and Shopify.

Key Features of MySQL

• Free to Use: MySQL is open-source, so that you can download, install, and use it without any licensing costs. This allows you to use all the functionalities a robust database management system provides without many barriers. However, for large organizations, it also offers commercial versions like MySQL Cluster Carrier Grade Edition and MySQL Enterprise Edition.
• Scalability: Suitable for both small and large-scale applications.
• MySQL runs on various platforms, including Windows, Linux, macOS, and Unix, making it versatile for different environments and use cases.
• MySQL is optimized for high performance, with capabilities like in-memory tables, query caching, and indexing. It can handle large datasets with low response times.

Another key feature of MySQL is MySQL Sharding. Learn how it works to be on top of your MySQL data.

What is Snowflake?

Snowflake is a cloud-based data warehousing platform designed for high performance and scalability. Unlike traditional databases, Snowflake is built on a cloud-native architecture, providing robust data storage, processing, and analytics capabilities.

Key Features of Snowflake

• Cloud-Native Architecture: Fully managed service that runs on cloud platforms like AWS, Azure, and Google Cloud.
• Scalability and Elasticity: Automatically scales compute resources to handle varying workloads without manual intervention.
• Snowflake integrates with data science platforms and machine learning frameworks like Python, R, Spark, and TensorFlow. It also supports Snowpark, a feature that allows developers to build and run data applications directly in Snowflake using Python, Java, and Scala.
• With Snowflake’s zero-copy cloning, you can create clones of databases, schemas, or tables without duplicating the underlying data.

You can check out some more additional features of Snowflake to get a better understanding of how Snowflake works.

Why move MySQL data to Snowflake?

• Performance and Scalability: MySQL may experience issues managing massive amounts of data and numerous user queries simultaneously as data quantity increases. Snowflake’s cloud-native architecture, which offers nearly limitless scalability and great performance, allows you to handle large datasets and intricate queries effectively.
• Higher Level Analytics: Snowflake offers advanced analytical features like data science and machine learning workflow assistance. These features can give you deeper insights and promote data-driven decision-making. 
• Economy of Cost: Because Snowflake separates computation and storage resources, you can optimize your expenses by only paying for what you utilize. The pay-as-you-go approach is more economical than the upkeep and expansion of MySQL servers situated on-site.
• Data Integration and Sharing: Snowflake’s powerful data-sharing features make integrating and securely exchanging data easier across departments and external partners. This skill is valuable for firms seeking to establish a cohesive data environment.
• Streamlined Upkeep: Snowflake removes the need for database administration duties, which include software patching, hardware provisioning, and backups. It is a fully managed service that enables you to concentrate less on maintenance and more on data analysis.

You can also move data from GCP MySQL to Snowflake within minutes for seamless data integration.

Method 1: Best Method to Migrate Data from MySQL to Snowflake – Using Hevo

Step 1.1: Configure MySQL as your Source

Step 1.2: Configure Snowflake as your Destination

You have successfully connected your source and destination with these two simple steps. From here, Hevo will take over and move your valuable data from MySQL to Snowflake. 

Advantages of using Hevo

• Auto Schema Mapping: Hevo eliminates the tedious task of schema management. It automatically detects the schema of incoming data and maps it to the destination schema.
• Incremental Data Load: Allows the transfer of modified data in real-time, ensuring efficient bandwidth utilization on both ends.
• Data Transformation: It provides a simple interface for perfecting, modifying, and enriching the data you want to transfer.

Method 2: How to Connect MySQL to Snowflake using Custom Code

Prerequisites

• You should have a Snowflake Account. If you don’t have one, check out Snowflake and register for a trial account.
• A MySQL server with your database. You can download it from MySQL’s official website if you don’t have one.

Let’s examine the step-by-step method for connecting MySQL Snowflake using the MySQL Application Interface and Snowflake Web Interface. 

Step 2.1: Extract Data from MySQL

• I created a dummy table called cricketers in MySQL for this demo. 

• You can click on the rightmost table icon to view your table. 

• Next, we need to save a .csv file of this table in our local storage to later load it into Snowflake.  
• You can do this by clicking on the icon next to Export/Import. 
• This will automatically save a .csv file of the table that is selected on your local storage.

Step 2.2: Create a new Database in Snowflake

• Now, we need to import this table into Snowflake. 
• Log into your Snowflake account, click Data>Databases, and click the +Database icon on the right-side panel to create a new database. 
• For this guide, I have already made a database called DEMO.

Step 2.3:  Create a new Table in that database

• Now click DEMO>PUBLIC>Tables, click the Create button, and select the From File option from the drop-down menu.

• A Dropbox will appear where you can drag and drop your .csv file. 
• Select and create a new table and give it a name. 
• You can also choose from existing tables, and your data will be appended to that table.

Step 2.4: Edit your table schema

• Click next. In this dialogue box, you can edit the schema.
• After modifying the schema according to your needs, click the load button. 
• This will start loading your table data from the .csv file to Snowflake.

Step 2.5: Preview your loaded table 

• Once the loading process has been completed, you can view your data by clicking the preview button.

Note: An alternative method of moving data is to use Snowflake’s COPY INTO command which allows you to load data from other sources into your Snowflake Data Warehouse. You will have to write SQL Queries to connect your data from your local storage into the target table in Snowflake. Finally, you can execute your COPY INTO statement to start loading your MySQL data into Snowflake.

Limitations of Manually Migrating Data from MySQL to Snowflake

• Error-prone: Custom coding and SQL Queries introduce a higher risk of errors potentially leading to data loss or corruption.
• Time-Consuming: Handling tables for large datasets is highly time-consuming.
• Orchestration Challenges: Manually migrating data needs more monitoring, alerting, and progress-tracking features.

Use Cases of Migrating Data from MySQL to Snowflake

1. Advanced Analytics: Moving data to Snowflake enables complex analytics and machine learning, as Snowflake can handle large-scale queries and workloads better than traditional MySQL databases.
2. Real-Time Data Insights: Snowflake’s architecture supports real-time data processing, which is ideal for businesses that need up-to-date insights, like customer behavior analysis or inventory management.
3. Data Consolidation: Snowflake can act as a centralized data warehouse, consolidating data from multiple MySQL databases and other sources, making it easier to analyze data from across the organization.
4. Scalability Needs: As data grows, Snowflake’s elastic scaling allows businesses to handle increased storage and compute requirements without the limitations of traditional MySQL databases.
5. Integration with BI Tools: Snowflake integrates smoothly with many business intelligence tools, making it easier to create data visualizations, dashboards, and reports compared to working directly in MySQL.

You can check out this detailed, easy-to-understand guide to Snowflake migration to easily sync your data into Snowflake.

Conclusion

You can now seamlessly connect MySQL to Snowflake using manual or automated methods. The manual method will work if you seek a more granular approach to your migration. However, if you are looking for an automated and zero solution for your migration, book a demo with Hevo.

See how to connect Azure MySQL to Snowflake for optimized data handling. Explore our guide for clear instructions on setting up the transfer.

FAQ on MySQL to Snowflake