By Tamara Astakhova, Sr. Partner Solutions Architect – AWS
By Brenner Heintz, Lead Technical Product Marketing Manager – Fivetran

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Data is growing exponentially and organizations rely on this huge amount of data to drive accurate analysis, prediction, and better decision making.

Companies are looking for a way to automate scalability, have flexibility, and simplify the administration and operational efforts of their data and analytics infrastructure so they can focus more on the business. At the same time, they want to optimize cost and performance to meet the demands of today’s business environments.

Amazon Redshift Serverless offers a number of benefits over traditional data warehouses, such as automatic scaling without having to manage infrastructure, built-in high availability, and a pay-for-use billing model to increase agility and optimize costs.

In this post, we will demonstrate how Fivetran can power data movement from both inside and outside a customer’s Amazon Web Services (AWS) environment and load/centralize all the data into Amazon Redshift Serverless. These processes significantly help organizations make data-driven decisions with reliable, high volume data integration that scales.

Fivetran is an AWS Specialization Partner and AWS Marketplace Seller with the Amazon Redshift Service Ready designation and Data and Analytics ISV Competency. Fivetran improves the accuracy of data-driven decisions by continuously synchronizing data from source applications to any destination, allowing analysts to work with the freshest possible data.

To accelerate analytics, Fivetran automates in-warehouse transformations and programmatically manages ready-to-query schemas.

About Amazon Redshift Serverless

Amazon Redshift Serverless makes it easy to run and scale analytics without having to manage your data warehouse infrastructure. Data scientists, developers, and data analysts can access meaningful insights and build data-driven applications with zero maintenance.

Amazon Redshift Serverless automatically provisions and intelligently scales data warehouse capacity to deliver fast performance for even the most demanding and unpredictable workloads, and you pay only for what you use. Just load data and start querying in your favorite business intelligence (BI) tools, build machine learning (ML) models in SQL, or combine your data with third-party data for new insights.

Existing Redshift customers can migrate their clusters to Amazon Redshift Serverless using the Redshift console or API without making changes to their applications.

Fivetran Integration

To get started with data analysis using Amazon Redshift Serverless, you need to extract the data from wherever it currently resides and load it into AWS. Fivetran is an automated data movement company and has over 250 connectors to all types of data sources: applications, databases, events, files, and functions. For landing your data in AWS, Fivetran supports both Amazon Redshift and Amazon Simple Storage Service (Amazon S3) as destinations.

To connect your data to Amazon Redshift using Fivetran, take the following steps:

  • From the Fivetran dashboard, choose Destinations from the left navigation bar.
  • Click Add destination, give your destination a unique name, and click Add.


Figure 1 – Add destination form.

  • Type “Redshift” in the search bar, choose Redshift from the list of destinations, and click Select.


Figure 2 – Set up Amazon Redshift as a destination.

  • The setup guide for the Redshift destination is shown on the right side. Follow the instructions to allow Fivetran to connect to Redshift directly with an SSH tunnel or with AWS PrivateLink. For additional information, visit this AWS blog post and documentation. In this example, we’ll connect directly so we’ll create a rule in a security group that allows Fivetran access to our Redshift cluster instance and port.
  • Enter the endpoint details for your Redshift data warehouse into Fivetran and click Save & Test.


Figure 3 – Amazon Redshift connection settings.

  • Now that the Redshift destination is set up, choose a data source to connect. For our purposes, we’ll connect to Salesforce so select Salesforce from the list and click Set up.


Figure 4 – Set up a source.

  • Enter the name of your destination schema and click Authorize. You’ll be asked to sign into Salesforce.
  • Now that we are ready to synchronize our data, so choose Sync now.
  • Your data is now syncing automatically, and can be queried with Amazon Redshift Serverless data warehouse.


Figure 5 – Data synchronization in Fivetran.


Integration of Fivetran with Amazon Redshift Serverless helps customers accelerate their journeys to modern data architecture. You can set this up in minutes and easily connect 190+ data sources including Salesforce and NetSuite.

With this integration, customers can transform data in a high-performance extract, load, transform (ELT) architecture, where the processing is done within Amazon Redshift Serverless itself rather than moving data in and out. This helps to automate connectivity with all of your data sources, no matter their API and schema changes.

Sign up for a free 14-day trial of Fivetran, and learn more about Fivetran in AWS Marketplace.


Fivetran – AWS Partner Spotlight

Fivetran is an AWS Partner and fully managed data movement platform that automatically ingests and centralizes data from hundreds of sources into ready-to-analyze schemas.

Contact Fivetran | Partner Overview | AWS Marketplace