Direct to Snowflake CDC

In the business of data engineering, seamless data loading is believed to be one of the most mundane but necessary engineering efforts. Timely, accurate, and efficient data movement can be the difference between success and stagnation. 

With the vast majority of modern data teams preferring to harness the power of Snowflake for their cloud platform, real-time data loading is absolutely paramount. That’s why Matillion; 2022 Snowflake Data Integration Partner of the Year, has enabled CDC loading directly into Snowflake in latency-free fashion from the most commonly used databases.

What is CDC? 

Change Data Capture is a method of database ‘extract’ and ‘load', capturing every change and loading the data to Snowflake in near real-time. By realizing change in data, users are able to perform use cases that they would not previously have access to, such as financial reporting and audit. For more information, read our comprehensive blog on change data capture (CDC), what it is, its importance and examples. 

Why CDC? 

• Near Real-Time Updates: CDC stages data directly within Snowflake, ensuring that your tables update in near real-time. No more waiting for batch updates.
• Totality: CDC enables the loading of all data changes, without missing a beat.
• Efficiency & Speed: CDC loads data directly from Matillion's Data Productivity Cloud to Snowflake, eliminating intermediaries that could slow down the process.
• Flexibility: Matillion offers the freedom to choose your data loading method, supporting both native loading and standard AVRO files.

Want to see Matillion’s direct connection to Snowflake in action? Senior Product Manager Johnathan Law walks through an example load in this short video:

By providing CDC loading directly into Snowflake, Matillion enables data practitioners of all skill levels to capture every single change to their production or analytics database. 

Start a Matillion trial and begin loading your data into Snowflake today!

– Matillion CDC also enables loading directly into a storage bucket, such as Amazon S3, Azure Blob, and Google Cloud Storage for users that prefer an immutable history of their data in Avro format. –