A Comprehensive Guide to Snowflake Migration: Best Practices and Strategies

Snowflake is a cloud data warehousing solution that has become popular for companies with large data volumes.

However, moving databases from an existing data platform to Snowflake can be complicated. You may face challenges in adapting existing pipelines that require custom code or integrating data from legacy systems to Snowflake’s environment.

This article will provide you with a complete overview of the procedure, along with recommendations and strategies to ensure a seamless Snowflake migration.

An Overview of Snowflake Data Warehouse

• Snowflake is a popular data warehouse that provides that provides cloud computing and storage functions. Its decoupled architecture allows the compute and storage layers to be scaled independently, giving you flexibility to manage your data. 
• Snowflake is a software as a service (SaaS) that may be hosted on Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP). Snowflake runs entirely on public cloud infrastructure, offering exceptional resilience and minimal maintenance.

Why Migrate to Snowflake?

Let’s discuss the main reasons for Snowflake migration before moving on to the migration process:

• Specifically Designed for the Cloud: Snowflake is a cloud-native data platform with infinite scalability. It can manage any data volume without the need for on-premises infrastructure, eliminating capacity concerns and streamlining resource management.
• Getting Rid of Data Silos: Snowflake provides a single source of truth for all data, integrating data from multiple sources into a single platform. This lets you integrate data seamlessly, collaborate effectively across your company, and make data-driven decisions.
• Scalability: Snowflakes’ architecture allows dynamic resource allocation, adapting to changing workloads to maintain high performance. It ensures that resources scale efficiently to match organizational needs.
• Improved Efficiency: Snowflake’s advanced architecture supports real-time analytics and rapid query execution. Separate computing and storage layers enable swift data loading and parallel processing.

How to Migrate Data to Snowflake?

Let’s look at the data migration to Snowflake with step-by-step instructions. 

Understand the Data

• Identify Data Patterns: Look for inconsistencies or irregularities.
• Classify Data: Organize data based on importance.
• Assess Data Quality: Ensure data is accurate and usable.
• Understand Data Relationships: Analyze complex data dependencies.

Select a Method for Migration

Selecting a Snowflake migration strategy is the next step after data analysis. Here are some methods you might want to think about:

a) Manual Migration Using Snowsight

• What It Is: Migrate data manually using Snowsight, Snowflake’s IDE.
• Best For: Small data sets.
• Limitations:
  • Data Volume: Poor performance for data exceeding 1 million rows.
  • Pricing: Additional costs may apply based on membership and usage.

b) Migration with Snowflake’s COPY INTO Command

• What It Is: Use Snowflake’s COPY INTO command to move data in real time.
• Best For: Larger datasets or automated transfers.
• Limitations:
  • Schema Matching: Must match source and target schemas precisely.
• Security Configuration: Requires proper setup to avoid security issues.

Select & Split Data

• After choosing your migration to the Snowflake technique, the next step is to split the data using a file splitter. This lowers the possibility of errors and streamlines the migration procedure.

Stage the Data

• Next, you must migrate your data to the Snowflake staging area. For this to work, you’ll need the SnowSQL command line tool, which you can easily download from the Snowflake platform.
• You can employ the zqvq command to easily stage local files for loading onto a Snowflake stage. 

Auto-Compress Files

• Remember to auto-compress local files in Snowflake to increase speed while staging them. For the best results, check to see if the files have been explicitly compressed using GZIP format.

Transfer the Data

• During this step, cloud migration configures the Snowflake environment and initiates the migration procedure.
• After configuring databases, warehouses, and accounts according to your requirements, you can transfer your previous system’s data to Snowflake.

Verify Cloud Migration

• Data migration testing is essential to ensure that your migrated data in Snowflake is accurate, accessible, and ready for use.

What are the Best Practices for Migrating Data to Snowflake? 

Let’s explore the Snowflake migration best practices that you can follow:

• Accelerate Snowflake throughput by obtaining data only from secondary or read-only instances. You can load backup files from production to a lower environment and extract datasets if a read-only instance isn’t available.
• Utilizing native extractors from the system and storing the extracted data on a staging server or NFS will speed up the extraction process.
• Use the appropriate text delimiter tool for your dataset to prevent data corruption during extraction.
• You must conduct a proof of concept during your analysis phase to determine the windows of maximum throughput during peak, non-peak, and weekend hours.
• You must choose the maximum accessible bandwidth rather than the total capacity because several projects sometimes share network bandwidth.
• Consider device-based data transfer if you have large data volumes, slow speed, and generally short timelines.
• For best throughput, utilize native Snowflake data loader utilities. The error-handling features of Snowflake native loaders can also help you quickly find issues in the data load.
• Employ different data warehouses to load data more affordably. Based on the volume of data you have, size the warehouse and set auto-scaling policies with the ability to pause and resume operations. On your Snowflake account, establish resource monitoring and set compute, credit limit, and notification triggers.

Learn More About: Snowflake On Premise Comparisons

Efficiently Integrate Data to Snowflake Using Hevo Data

Efficient data integration to Snowflake is crucial for maintaining data quality and supporting real-time analytics. To save time and energy, you can use Hevo, a real-time ELT no-code data integration platform that has automated data pipelines adaptable to your needs.

It assists you in transforming and enriching your data in a cost-effective manner by integrating with 150+ data sources (40+ free sources). Here are some of Hevo’s top features:

Incremental Data Load: Hevo ensures effective bandwidth consumption by enabling near real-time transfers of updated data. Thus, your Snowflake database remains up-to-date with minimal latency, enhancing the overall performance.

Data Transformation: Hevo offers drag-and-drop and Python-based data transformation tools that let you clean and modify data before importing it into the desired location. This capability is particularly advantageous for Snowflake migration, as it ensures that your data is not only seamlessly transferred but also optimized and analysis-ready upon arrival.

Automated Schema Mapping: Hevo detects the incoming data format and replicates it to the destination schema, automating the schema management process. Based on your data replication needs, you can choose between full or incremental mappings. This feature helps create accurate data structures in your Snowflake migration process.

Conclusion

1. Migrating to Snowflake can significantly enhance your data management and analytics capabilities, but the process involves various challenges that need careful consideration.
2. Manual migration methods can be time-consuming, error-prone, and resource-intensive, often leading to disruptions and inefficiencies. In contrast, Hevo provides a streamlined, automated approach to Snowflake migration, effectively addressing these challenges.
3. Follow essential steps for successful data migration to Snowflake, ensuring minimal downtime and efficient performance. Explore details at Snowflake Migration Best Practices.

Want to take Hevo for a spin? Sign Up for a 14-day free trial and experience the feature-rich Hevo suite firsthand. Also, check out our unbeatable pricing to choose the best plan for your organization.

Share your experience of Snowflake migration in the comments section below!

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