Organizations are constantly on the lookout for simple solutions to integrate their company data from several sources into a centralized location, then analyze it to make informed decisions. This process is termed Data Integration. One of the most popular Data Integration techniques is ETL (Extract, Transform and Load). You will get to know more about the ETL procedure in the further sections.

This article aims to help you discover various approaches to perform Salesforce ETL. It also highlights the limitations and challenges that might come your way. The objective is to share enough knowledge to help you choose the best approach for your use case. You will also explore the Salesforce ETL tools in the further sections.

Introduction to Salesforce

salesforce ETL

Salesforce is the most widely used cloud-based CRM platform. It stores all your customer data, contact data, marketing leads, and many more. Combining this with data from many other sources in your Data Warehouse can deliver valuable insights for your business. The first step, however, would be to get all the data from Salesforce into a Data Warehouse of your choice. In the further section, you will get to know the methods used for Salesforce ETL.

To know more about Salesforce, visit this link.

Methods to move data from Salesforce to Data Warehouse

Method 1: Setting up Salesforce ETL Using Hevo Data

With Hevo, Salesforce ETL becomes a cakewalk. Hevo is fully automated so you do not have to write custom scripts or concern yourself with code maintenance. Hevo moves data from Salesforce to any Data Warehouse like Redshift, BigQuery, or Snowflake with 100% reliability, consistency, and for free. This will rid you of investing time and resources in overseeing data quality.

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Method 2: Setting up Salesforce ETL Using Custom ETL Scripts

The custom scripting approach holds the promise of control and flexibility. A bunch of talented developers can write scripts to get data on the fly. This, however, comes with certain risks that are discussed more in detail later.

Methods to Set up Salesforce ETL

Users can use one of the two methods for setting up the Salesforce ETL:

Method 1: Copying your data from Salesforce to your Data Warehouse using Hevo

With Hevo, Salesforce data can be moved to any warehouse in 2 simple steps:

Step 1: Connect your Salesforce account by authorizing it.

Copying your data from Salesforce to your Data Warehouse using Hevo
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Step 2: Select and authenticate the Warehouse to which you want to move this data

Choosing the Desired Data Warehouse Destination in Hevo
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Advantages of using Hevo for Setting up Salesforce ETL

Some of the advantages of using Hevo for setting up Salesforce ETL include:

  1. Secure: Hevo has a fault-tolerant architecture that ensures that the data is handled in a secure, consistent manner with zero data loss.
  2. Schema Management: Hevo takes away the tedious task of schema management & automatically detects the schema of incoming data and maps it to the destination schema.
  3. Minimal Learning: Hevo, with its simple and interactive UI, is extremely simple for new customers to work on and perform operations.
  4. Hevo Is Built To Scale: As the number of sources and the volume of your data grows, Hevo scales horizontally, handling millions of records per minute with very little latency.
  5. Incremental Data Load: Hevo allows the transfer of data that has been modified in real-time. This ensures efficient utilization of bandwidth on both ends.
  6. Live Support: The Hevo team is available round the clock to extend exceptional support to its customers through chat, email, and support calls.
  7. Live Monitoring: Hevo allows you to monitor the data flow and check where your data is at a particular point in time.
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Method 2: Copying your data from Salesforce to your data warehouse using custom scripts

Your Salesforce data is accessed using Salesforce’s vast range of APIs. The APIs needed by you will be determined by the use cases that you are solving. The broad steps are as follows:

Step 1: Identify your Data

Start by familiarizing yourself with Salesforce’s developer guide. Then take a deep dive into Salesforce’s universe of APIs. The most succinct description of these is found here in Salesforce documentation

Step 2: Pull your Data

Let’s say you choose to work the REST API. You can use tools like CURL or Postman to fetch your data. The server will typically respond with a list of available resources in JSON or XML, depending on what you asked for. The Salesforce REST API supports a language called Salesforce Object Query Language (SOQL) for executing arbitrarily complex queries. Again, the result can be either in JSON or XML. More information on SOQL can be found on the Salesforce SOQL Reference pages. Alternatively, you may decide to work with the SOAP API, in which case you first create a SOAP client, then set up a Web Services Connector to communicate with Salesforce.

You may also want to use Salesforce’s streaming API, so your data is always current. This powerful streaming mechanism is not without constraints. For further reading, Salesforce documentation on Streaming API has all the information you need.

Whichever route you choose, we recommend using JSON, as most popular data warehousing solutions natively support it. When you have decided on the API or APIs you will need to:

  1. Select the data you need to extract from the API.
  2. Set up a data warehouse repository and map the Salesforce data to this.
  3. Transform your data into the repository.
  4. Load your transformed data into your warehouse

Step 3: Data Staging

If you are using Google BigQuery as your data warehouse, you may decide to use Google Cloud Storage as your repository or staging area for loading your data into a warehouse. Alternatively, if you are using Amazon Redshift or Snowflake you may opt for Amazon S3 as your data repository.

Step 4: Data Type Mapping

You need to make sure the data types returned by the API call are supported by your data warehouse. You can learn about data transformation and mapping for the current big names in cloud-based warehouses using these links:

Step 5: Data Warehouse Schema

You need to design the schema for your Data Warehouse (Redshift, Snowflake, or BigQuery) and map the data from your data source for maximum performance.

Step 6: Loading the Data

How you do this depends on which data bucket or repository you use and your data warehouse. For instance, if you are using Google BigQuery, you can use either BigQuery’s command-line tool or any cloud SDK. If you are using Amazon S3 you will need to run a COPY command to get data into your warehouse.

This overview of getting your data from Salesforce into a cloud-based warehouse is just a cursory look at the primary steps involved. 

Challenges of Setting up Salesforce ETL Using Custom ETL Scripts

Administrators and engineers write scripts to solve problems. simplify processes and improve performance. Unfortunately, this often evolves into an over-reliance on scripting. Your entire scripting universe can grow into an unsustainable burden. Below are the challenges that can be faced while setting up Salesforce ETL:

  1. Error Handling: Glaring errors that are found in your scripts get fixed early, but there are more insidious errors that often are not discovered until a process is well underway. What do you do when an error causes part of or even your entire data flow to stop?
  2. Real-time Salesforce ETL: The steps mentioned above only help you load the data one-time or periodically. The process to get your Salesforce data to your warehouse is cumbersome and effort-intensive.
  3. Schema Changes: What is your procedure for updating schema at the warehouse in response to changes in the Salesforce API?
  4. Source/Destination Unreachable: How do you plan to prevent data loss if Salesforce or your Data Warehouse is not reachable? 
  5. Documentation: Are your scripts documented and cataloged? When engineering resources move in and out of the organization, this becomes a key aspect for the organization.
  6. Addition Data Requests: Would you have ready engineering resources to modify and update the scripts when there is a request for more data? Given this data is supercritical for your business teams, it would be smart to account for update requests.

All the above limitations can be handled by opting for a Salesforce ETL platform that works out of the box. Here is how Hevo can help:

Choosing the Best Salesforce ETL Tool

Choosing the best tool from the plenty of Salesforce ETL is one of the difficult tasks. However, there are some features that you should look for in the Salesforce ETL tools. Some of these features include:

  • No code platforms should be preferred that do not require technical backgrounds.
  • The ETL tool should provide an adequate number of integrations with Data Warehouses, Databases, CRMs, etc.
  • An appealing and easy-to-use interface should be present.
  • The ETL platform should be secured enough and should comply with regulations established by CCPA, GDPR, and other laws

Best Tools for Salesforce ETL

With the advancement in technologies, there is a surge in the tools for Salesforce ETL. Some alternatives other than Hevo for Salesforce ETL include:

1) Xplenty

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Xplenty is one of the popular ETL tools among Experienced as well as beginner Data Analysts. It provides an easy-to-use drag and drops environment. Moreover, Low-code scripts can also be written by users with some coding experience to do certain tasks.

Salesforce Databases and Data Warehouses are compatible with Xplenty. You can easily modify data before sending it to other databases like MySQL, Amazon Redshift, Google BigQuery, or even back into Salesforce with a two-way integration feature by adding Xplenty to your software package. It can be one of the ideal choices for the Salesforce ETL.

2) Talend

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Talend is also a popular ETL tool among many users. It provides strong data governance and is mostly suitable for large enterprises. However, certain drawbacks are also associated with Talend. Talend usually requires strong technical skills to operate it. Moreover, it is not a suitable choice for Sales and Marketing Analytics.

3) Stitch

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Stitch is also one of the popular Salesforce ETL tools that comes with many great features. However, it also requires a technical background from the users’ side, similar to that of Talend discussed above.

If you are a technically sound person, then it can be a great choice for you. This platform is mostly used by developers or Software professionals as it gives full control over the data.


Salesforce ETL tool like Hevo is key to enabling data agility, performance, and reliability in an organization. Hevo’s fault-tolerant, dependable data integration platform gives you a trouble-free environment in which you can move data from any source to any destination.

Businesses can use automated platforms like Hevo Data to set this integration and handle the ETL process. It helps you directly transfer data from a free data source such as Salesforce, etc., to a Data Warehouse, Business Intelligence tools, or any other desired destination in a fully automated and secure manner without having to write any code and will provide you a hassle-free experience.

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Share your experience of learning about Salesforce ETL in the comments section below!

Customer Experience Engineer, Hevo Data

Skand, with 2.5 years of experience, specializes in MySQL, Postgres, and REST APIs at Hevo. He efficiently troubleshoots customer issues, contributes to knowledge base and SOPs, and assists customers in achieving their use cases through Hevo's platform.

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