The Snowflake cloud data warehouse has become widely recognized as a flexible, high-performing, and scalable solution for both data warehousing and analytics needs. This article will explore how to migrate a database to Snowflake cloud data warehouse and also provide insights into some best practices for the migration.
Page Content
Introduction
As the Snowflake cloud data warehouse gains popularity, many organizations are considering migrating their databases to it. However, the migration process can be complex, especially if you are not familiar with Snowflake. This article discusses the best practices and tips for a successful database migration to Snowflake, which can be used for Oracle, Netezza, Teradata, SQL Server, and other database migrations. Learn how to optimize your migration process and take advantage of Snowflake’s scalability, performance, and flexibility.
Preparing for Migration
Before you start migrating your database, you need to prepare by analyzing your current database, identifying the data to be migrated, mapping the data to Snowflake schema, and ensuring data security. This will help you avoid any data loss or security breaches during the migration process.
Assessing the Existing Solution that Needs to be Migrated:
- Determine the Snowflake accounts that already exist or need to be created.
- Take an inventory of the databases that need to be migrated.
- Identify the database objects that need to be migrated.
- Document the processes and tools that are used to populate and pull data from the existing solution.
- List the security roles, users, and permissions that are in place in the existing solution.
- Create a current architecture diagram of the existing solution.
Migrating to Snowflake
Once you’ve prepared for the migration, you can start migrating your data to Snowflake. You need to choose a migration method, set up the Snowflake environment, migrate the data, and validate the Snowflake data. This requires careful planning, testing, and monitoring to ensure a successful migration.
Below are the steps involved in the database migration process:
- Set up the Snowflake environment.
- Convert the source database DDL’s to their Snowflake equivalent DDL’s.
- Migrate the data to Snowflake.
- Validate the migrated data.
- Convert the source database queries to their Snowflake equivalent.
- Convert SELECT statements and views to Snowflake equivalent.
- Convert Stored Procedures to Snowscript stored procedures.
- Convert any Spark application to its Snowpark equivalent code.
Please note that this list is not exhaustive, and you may need to perform additional steps based on your specific source database.
Best Practices for Database Migration to Snowflake
To ensure a successful Snowflake migration, you need to follow some best practices, such as file sizing and format, minimizing downtime, planning for scalability, testing the migration process, and monitoring the migration progress. By following these best practices, you can avoid common pitfalls and ensure a smooth migration process.
Best Practices for File Sizing and Format
It is important to consider file sizing and format when migrating databases to Snowflake. Here are some of the best practices for file sizing and format:
- Compressed data files in the range of 100-250 MB are recommended for running load operations in parallel.
- The individual row size limit for the VARIANT data type is 16 MB.
- For continuous data loads using Snowpipe, the recommended compressed data file size is 100-250 MB.
- Use the ENCODING file format option to specify the character set for the data files.
- Enclose fields that contain delimiter characters in quotes (single or double).
- Avoid using embedded characters such as commas (e.g., 123,456) in the data files.
Best Practices for Data Transfer
Best Practices for Data Transfer involve using the right approach to move data from the source database to Snowflake. Here are some of the best practices:
- Consider using bulk data transfer if:
- The existing warehouse has highly integrated data.
- There is a single independent, standalone data mart.
- The data and processes are well-designed using standard ANSI SQL.
- There is a need to move off legacy equipment quickly.
- Consider using a staged data transfer approach if:
- The warehouse platform has many independent data marts and other data applications that can be moved independently over time.
- Critical data and processes within the data warehouse no longer perform well and require re-engineering.
- New business requirements cannot be met by reworking legacy processes.
- There are changes to the data ecosystem, such as new data ingestion, BI, or visualization tools.
Best Practices for Running Source and Snowflake Databases
Running the source and Snowflake databases in parallel is a best practice that helps in validating data and ensuring that the migration process goes smoothly. Here are some of the best practices for running source and snowflake databases:
- Initially, it is recommended to set up data loading schedules in parallel with the existing source database.
- Once validation is completed, the source database loading process can be decommissioned.
- For some time, it is advisable to run the source database and Snowflake in parallel until the validation process is completed.
Best Practices for Temporary and Transient Tables
When migrating databases to Snowflake, it is essential to consider best practices for temporary and transient tables. Here are some of the best practices:
- To minimize storage costs, create a temporary table if it is required only within the current session.
- Snowflake recommends explicitly dropping large temporary tables once they are no longer needed in the session.
- Create transient tables instead of permanent tables if fail-safe is not required as there will be no additional costs for maintaining data for disaster recovery purposes.
Tips for Successful Snowflake Migration
In addition to following best practices, there are some tips that can help you ensure a successful Snowflake migration, such as backing up the data, training the team, communicating with stakeholders, and seeking Snowflake help if necessary. These tips can help you overcome any challenges or obstacles during the migration process and ensure a successful outcome.
Conclusion
Migrating your database to Snowflake can be a complex and challenging process, but by following the best practices and tips outlined in this article, you can ensure a successful migration. Whether you’re looking to improve your data warehousing or analytics capabilities, Snowflake can help you achieve your goals.
Related Articles,
Hope this helps 🙂