AWS Partner Network (APN) Blog
Use Matillion Data Loader for Change Data Capture Loading to Amazon Redshift Serverless
With Amazon Redshift Serverless, users can run and scale analytics workloads seamlessly, paying only for the compute and storage resources they consume. Businesses often have a need to use change data capture (CDC) to quickly and easily load incremental data to data warehouses. Learn how to load data easily into Amazon Redshift Serverless using Matillion Data Loader, and see an example of CDC loading from PostgreSQL to Amazon Redshift Serverless as the destination.
How to Use Matillion Data Loader for Batch Loading Data to Amazon Redshift Serverless
Amazon Redshift Serverless makes it easier to run and scale analytics without the burden of managing infrastructure. Learn how you can use Matillion Data Loader to extract data from source systems and load it to Amazon Redshift Serverless without having to worry about coding or managing infrastructure. Matillion Data Loader enables organizations that have data coming in from an ever-increasing number of sources and need faster, simpler access to insights and analytics.
Building a Serverless Trigger-Based Data Movement Pipeline Using Apache NiFi, DataFlow Functions, and AWS Lambda
Organizations have a wide range of data processing use cases, collecting data from variety of sources, transforming it and loading it to different destinations to fulfill diverse business needs. Learn how DataFlow Functions, combined with the serverless compute services provided by AWS Lambda, enables developers to implement a wide spectrum of use cases using the low-code NiFi flow designer user interface, and deploy the flows as short-lived serverless functions.


