How to load data from Salesforce to Redshift: A definitive guide

How to load data from Salesforce to Redshift: A definitive guide

January 26, 2023
January 26, 2023
How to load data from Salesforce to Redshift: A definitive guide
In this guide, you will learn about various methods to transfer your data from Salesforce to Redshift.

Data integration is a critical part of any business's success. Moving data from Salesforce to Redshift can be difficult without the right technology and expertise. With the right tool set and an experienced team, it's possible to move data from Salesforce to Redshift quickly and accurately. Companies that take advantage of these solutions can save time and money, as moving data will be more accurate and reliable for later use. Without the proper solution in place, companies risk wasting time and resources on inaccurate data which could lead to disastrous results.

In this guide, you will learn about various methods to transfer your data from Salesforce to Redshift. You will also explore the limitations associated with manually loading your data and discover an easier alternative to this. Before we jump to that part, let’s get an overview of Salesforce and Redshift.


Introduction to Salesforce

Salesforce is a Customer Relationship Management, cloud-based platform which helps you to manage everything related to your customers from sales and marketing to generating reports to analyze your data. Furthermore, Salesforce users can easily integrate the platform with other applications. You can manage client relations, collaborate with your employees and partners, and save your data safely in the cloud. Dynamic dashboards, real-time analytics and enhanced collaboration make Salesforce a popular choice among businesses.

Introduction to Redshift

Amazon Redshift is a leading Data Warehouse platform that can store petabytes of data. It supports a Massively Parallel Processing (MPP) architecture that allows you to run many queries parallely, thereby providing exceptional performance. Redshift's flexible pay-as-you-use pricing structure lets users pay for the storage and instance type they leverage. With little effort on the part of the user, it offers a comprehensive range of security. 

High scalability and fast query processing continue to make Redshift one of the most well-liked Data Warehouses. When used in conjunction with a reliable ETL tool like Fivetran, Amazon Redshift, a data warehouse built for batch loads, can also be leveraged for near real-time data loads.

Methods to Load Data from Salesforce to Redshift

Salesforce generates data on leads, sales, and much more. When collected in a central data warehouse like Redshift, all of this data can be well utilized to forecast sales trends and allocate marketing and other expenses appropriately to increase profits.

To load your data from Salesforce to Redshift, you can either do it manually, that is by writing ETL scripts or use an easier alternative like Fivetran that helps you to load data within a few clicks. Let’s discuss these methods in detail below along with their benefits and limitations.

Method 1: Salesforce to Redshift Using the Fivetran tool

Fivetran is an automated cloud ETL (Extract, Transfer, Load) tool that helps move your data from various sources to data storage such as a data warehouse or a database. Fivetran provides Salesforce connectors for both production and sandbox environments.

Fivetran makes use of Salesforce APIs to load data into Redshift. Before you start setting up your Fivetran Salesforce connector, make sure you can access an active Salesforce account either Enterprise plan or higher, or you have purchased Salesforce API calls.

To setup up the Salesforce Redshift integration using Fivetran, we’ll divide it into two parts. First, set up Salesforce as a data source and second set up Redshift as the destination. 

1. Setting Up Salesforce in Fivetran

  • Enter the destination schema name of your choice in the connector setup form.
  • To authorize the API, click Authorize. The login page for Salesforce will be displayed.
  • To grant Fivetran permission to connect to your Salesforce account, sign in.
  • When you are back on the Fivetran interface, select Save & Test. From here, Fivetran will handle syncing your data from your Salesforce account.

Refer Salesforce Data Connector Setup Guide to read it in more detail.

2. Setting Up Redshift in Fivetran

  • Add Redshift as your destination type in Fivetran.
  • Enter the hostname in the ‘Host’ and ‘Port’ fields.
  • Next, enter the Database and user name.
  • Now, you need to choose an Authentication Type: PASSWORD or IAM. If you select IAM, enter the Role ARN you generated for your Redshift cluster.
  • Redshift provides 3 methods to connect your Redshift - directly, via SSH or via Private Link. Select one and follow the instructions listed on the page.
  • Next, choose the data processing location, and timezone and then click Save and Test. Your Salesforce Redshift integration is finally ready.

Refer to Redshift Destination Setup Guide to read it in more detail.

Salesforce to Redshift : Advantages of using Fivetran

Some of the advantages of using Fivetran are listed below:

  • Easy To Setup: As opposed to some other methods, like Airflow, which take a lot of work to set up right in the beginning, Fivetran connectors for data loading and extraction are relatively simple to set up and use.
  • Automated & Real-Time Sync: The connections from Fivetran guarantee data consistency and integrity by automatically adjusting to API and schema changes. It continuously syncs data across data sources and target warehouses.
  • Multiple Connectors: Fivetran enables teams to work more efficiently with fewer resources. Users can connect to more than 100 data sources using Fivetran's robust integration tools to consolidate their data.
  • Less Resource Management: Fivetran takes care of all the error recovery, incremental loading, and scheduling. As a result, your team will have lesser worries and can focus on other priority tasks.

Method 2: Salesforce to Redshift using Data Loader Export Wizard

Salesforce provides a Data Loader for the bulk import or export of data. It allows you to add, update, remove, or export Salesforce records. Both Windows and Mac OS support it. It can also handle files with up to 5 million records. However, this feature is available only in Enterprise, Performance, Unlimited, and Developer editions of Salesforce. 

To export data from Salesforce to Redshift, you will first need to download the CSV file from Salesforce using Data Loader, then import it to Amazon S3 and lastly load data from S3 to Redshift. These steps are detailed below:

1. Export Data from Salesforce using Data Loader Export Wizard

If you haven’t already installed the Data Loader on your system, you can refer to Installing Data Loader guide. Follow the steps below to export CSV file:

  • Open the Data Loader and then click on Export button.
  • Enter your Salesforce credentials and click on Log in and then click Next.
  • Choose a Salesforce object from which you want to export data. If the name of your object isn't mentioned, choose Show all Salesforce Objects to view every object you have access to.
  • Enter the name of the CSV file and click Next. You can either select an existing file or create a new file.
  • Now, you need to create a SOQL(Salesforce Object Query Language) query for the data export. Firstly determine which fields you want to export. Then specify the conditions if you want to filter your dataset. If none of the conditions are selected, all read access data is returned. Review the generated query and make any necessary modifications.
  • Now, click on Finish and then click Yes. Once the operation completes, a confirmation window will list down the results.
  • Click View Extraction to view the CSV file generated, or click OK to close the confirmation window.

2. Upload CSV File to Amazon S3

To upload Salesforce data into Amazon S3 follow the steps below:

  • Open your Amazon S3 Console and on click on Create Bucket option.
  • Now type in a unique S3 Bucket name and select a Region.
  • Next, click on Create.
  • Now, choose new bucket you just created, then click Actions button, and select Create Folder in the drop-down list. Name your folder.
  • From the drop-down list, choose the name of the data folder you just entered.
  • Now select Files wizard and choose Add Files.
  • Select the Salesforce CSV file you downloaded and click on Start Upload.

3. Load Data from Amazon S3 to Redshift

You must first create the tables if you haven't already done so for the data in Redshift. In addition, ensure that the Amazon Redshift COPY command has the necessary permissions to read the file objects stored in the Amazon S3 bucket. 

The following is the syntax of the COPY command:

COPY table_name [ column_list ] FROM data_source CREDENTIALS access_credentials [options] 

You must enter the following values in order to execute a COPY command:

  • Table Name: The table that the COPY operation will target in the data source.
  • Column List: By default, COPY inserts the fields from the source data into the table columns in the correct order. To map data fields to certain columns, you can optionally give a column list, which is a list of column names separated by commas.
  • Data Source: You must specify the name of the bucket and the location of the data files since we want to load data from Amazon S3.
  • Credentials: Here you must provide the AWS access credentials for an AWS user or an IAM user with the necessary rights in order to access the AWS resources that house the data to load.

Read Amazon Redshift COPY command to know more about the COPY command and how to use it to load data from Amazon S3 to Redshift. After importing your CSV files, you can delete the bucket from Amazon S3 or just the CSV files to reduce the expense of storing your file there. So, finally your data is loaded from Salesforce to Redshift.

Salesforce to Redshift : Disadvantages of Manually Loading Data  

Now that you have understood how to manually load data from Salesforce to Redshift using Salesforce Data Loader Export, let’s discuss the limitations associated with this method.

  • Data Export - Time Limitation: The Data Loader export wizard is not available if you have Salesforce Professional or Essentials. You can employ the Salesforce export backup data functionality in this case. Depending on your Salesforce edition, this tool lets you export data every 29 days or weekly. If you've recently used it, it might not be available.
  • Complex ETL Scripts: Writing tens of thousands of lines of code to replicate your data can be quite challenging and tedious. Moreover, the difficulty and expense associated are frequently underestimated.
  • No Syncing: The data you export from Salesforce is not dynamic. This means that Redshift will not automatically update to reflect any changes made to the underlying CSV files or new data added to Salesforce. Thus, the integration process must be carried out again each time data is updated in Salesforce.
  • Error-Prone: Transforming data when moving it between systems is a common practice. To make sure the data being imported has the right syntax and semantics, there may be content validation or enrichment. Your transformations could become labor-intensive when dealing with enormous data or complex data. Moreover, some errors might skip through and you will again need to check the whole transformation script.
  • Extensive Resources Required: You must keep track of any upgrades to Redshift or Salesforce. A mechanism for validating data is also necessary to guarantee accurate data replication. In today's agile environment, where resources are nearly always fully exploited and engaged, these tasks become a tremendous burden. To keep up with all the potential breakdowns, you will need to spend an extra amount of engineering resources. Consequently, there would be less room for taking on new tasks.

Looking at the disadvantages above, by know you might have understood that it takes a lot of knowledge, time, and labor to build an internal data pipeline and write complex ETL scripts, and there is a higher risk of error. Hence, choosing automated, near-real-time ETL tools such as Fivetran is an easier alternative. The benefits of Fivetran listed above help streamline the process of loading data from Salesforce to Redshift.


In this guide, you got an overview of Salesforce and Redshift. You also learned how to manually load your data from Salesforce to Redshift by using Salesforce Data Loader Export wizard. 

Manually performing this data migration provided challenges and could induce errors as already discussed above. Therefore, loading your data from Salesforce to Redshift using a cloud data pipeline like Fivetran will help save your day. There is no need for any coding because it can automatically export data from Salesforce CRM into a data warehouse like Amazon Redshift. You can also visit Connector Directory | Fivetran, to explore various other connectors supported by Fivetran.


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