How to Load Data from Salesforce to PostgreSQL?

Key Takeaways

Syncing Salesforce data to PostgreSQL moves your CRM data into a relational database for SQL analytics, custom app development, and BI reporting. The right approach depends on your technical expertise, sync frequency, and whether you need one-way replication or bidirectional sync.

Two ways to load Salesforce data into PostgreSQL:

• Hevo Data is best for teams that want automated, real-time sync with zero engineering overhead and no custom scripts to maintain
• Custom ETL Scripts is best for developers who need full programmatic control over data transformations, API logic, and scheduling

Broader options worth knowing:

• Managed ELT platforms like Skyvia, Weld, and CData Sync offer low-code alternatives with automated schema mapping and incremental updates
• Python libraries like dlt Hub give developers programmatic control to define and run Salesforce to PostgreSQL pipelines
• Bidirectional sync tools like Stacksync are worth evaluating if your team needs to read and write data back into Salesforce natively

Key consideration: Salesforce API limits must be managed carefully. Managed tools like Hevo handle this automatically. Custom scripts require manual rate limit handling which adds engineering overhead as data volumes grow.

Salesforce is the world’s number one CRM platform. According to IDC’s 2024 CRM market share report, Salesforce led all CRM vendors with a 20.7 percent market share, holding the top position for the 12th consecutive year. But for all its power as a CRM, Salesforce was not built for SQL analytics, custom app development, or BI reporting. That is where PostgreSQL comes in.

Moving Salesforce data into PostgreSQL gives your team a relational database optimized for querying, reporting, and building data-driven applications on top of your CRM data. The challenge is getting data there reliably, on a schedule, and without breaking every time Salesforce updates its schema.

This guide covers two proven methods to load Salesforce data into PostgreSQL, a no-code automated approach with Hevo and a custom ETL script method, so you can choose the right fit for your team and get started today.

Prerequisites for Salesforce to PostgreSQL Integration

Hevo Data:

• Active Salesforce account with data access
• PostgreSQL server version 9.4 or higher with database ready
• Hevo account with admin permissions
• Hevo’s IP addresses whitelisted in your PostgreSQL server configuration

Custom ETL Scripts:

• curl utility installed on your system
• Salesforce account with API access enabled
• PostgreSQL database with appropriate user permissions
• Basic knowledge of API calls and command-line tools

How to load data from Salesforce to PostgreSQL ?

There are two ways to load Salesforce data into PostgreSQL. The right choice depends on your team’s technical expertise, how often you need fresh data, and how much engineering effort you can invest.

• Method 1: Hevo Data is best for teams that want automated, real-time sync with zero engineering overhead and no custom scripts to maintain

• Method 2: Custom ETL Scripts is best for developers who need full control over data transformations, scheduling, and integration into existing workflows

Method 1: Using Hevo Data for Salesforce to PostgreSQL Integration

Pre-requisites:

• Active Salesforce account with data access
• PostgreSQL server (version 9.4 or higher) with database ready
• Hevo account with admin permissions

Step 1: Connect Salesforce as Your Data Source

Begin your Salesforce to PostgreSQL integration by linking your Salesforce account:

• Navigate to Hevo dashboard → CREATE PIPELINE → Select Salesforce as source

• Choose Production or Sandbox environment based on your requirements

• Login to Salesforce and click “Allow” to authorize Hevo’s data access

• Your Salesforce connection is now established and ready for configuration

Step 2: Configure Your Data Pipeline Settings

Set up how your Salesforce to PostgreSQL integration will handle data transfer:

• Enter a unique pipeline name (up to 255 characters) for easy identification
• Select historical sync duration (default 3 months, or choose “all available data”)

• Enable auto-sync for new Salesforce objects or manually control future object syncing
• Click CONTINUE to proceed with destination setup

Step 3: Prepare Your PostgreSQL Database

Ensure your PostgreSQL database is ready to receive Salesforce data:

• Create a dedicated database user with necessary privileges using: CREATE USER <username> WITH PASSWORD '<password>';
• Grant required permissions: GRANT CREATE, CONNECT, TEMPORARY ON DATABASE <database_name> TO <username>;
• Whitelist Hevo’s IP addresses in your PostgreSQL server configuration
• Verify your PostgreSQL server is accessible and running on the correct port (default: 5432)

Step 4: Connect PostgreSQL as Your Destination

Complete your Salesforce to PostgreSQL integration by configuring the destination:

• Go to DESTINATIONS → CREATE DESTINATION → Select PostgreSQL
• Enter connection details: database host, port (5432), username, password, and database name

• Configure optional security settings like SSH tunneling or SSL encryption if needed
• Enable table/column name sanitization to avoid naming conflicts between Salesforce and PostgreSQL
• Click TEST CONNECTION to verify setup, then SAVE & CONTINUE to activate your pipeline

Your Salesforce to PostgreSQL integration is now live! Data will automatically sync in real-time without any manual intervention required.

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Method 2: Using Custom ETL Scripts for Salesforce to PostgreSQL Integration

Custom ETL scripts provide complete control over your Salesforce to PostgreSQL data migration using Salesforce’s powerful APIs. This method is perfect for developers who need customized data transformations, specific scheduling requirements, or want to integrate the process into existing workflows. While it requires technical expertise, it offers maximum flexibility and can handle complex business logic during data transfer.

Pre-requisites:

• Salesforce account with API access enabled
• PostgreSQL database with appropriate user permissions
• Basic knowledge of API calls and command-line tools
• curl utility is installed on your system

Step 1: Authenticate and Extract Data from Salesforce

• Connect to Salesforce using SOAP API and extract your data through Bulk API for optimal performance:

• Login to Salesforce: Create a login.xml file with your credentials:

<?xml version="1.0" encoding="utf-8"?>

<env:Envelope xmlns:env="http://schemas.xmlsoap.org/soap/envelope/">

<env:Body>

<n1:login xmlns:n1="urn:partner.soap.sforce.com">

<n1:username>your_username</n1:username>

<n1:password>your_password_and_security_token</n1:password>

</n1:login>

</env:Body>

</env:Envelope>

• Execute login command and save the session ID:

curl https://login.salesforce.com/services/Soap/u/47.0 \

-H "Content-Type: text/xml; charset=UTF-8" \

-H "SOAPAction: login" -d @login.xml

Step 2: Create Bulk Job and Query Data

• Set up a Bulk API job to efficiently extract large datasets from Salesforce objects:

• Create job configuration (job.xml):

<?xml version="1.0" encoding="UTF-8"?>

<jobInfo xmlns="http://www.force.com/2009/06/asyncapi/dataload">

<operation>query</operation>

<object>Contact</object>

<contentType>CSV</contentType>

</jobInfo>

• Create the job and submit your query:

# Create job

curl https://your-instance.salesforce.com/services/async/47.0/job \

-H "X-SFDC-Session: your_session_id" \

-H "Content-Type: application/xml; charset=UTF-8" -d @job.xml

# Submit query batch

curl https://your-instance.salesforce.com/services/async/47.0/job/job_id/batch \

-H "X-SFDC-Session: your_session_id" \

-H "Content-Type: text/csv; charset=UTF-8" \

-d "SELECT Id, Name, Email, Phone FROM Contact WHERE LastModifiedDate > YESTERDAY"

• Close the job and retrieve the results:

# Close the job

curl https://your-instance.salesforce.com/services/async/47.0/job/job_id \

-H "X-SFDC-Session: your_session_id" \

-H "Content-Type: application/xml; charset=UTF-8" \

-d '<?xml version="1.0" encoding="UTF-8"?><jobInfo xmlns="http://www.force.com/2009/06/asyncapi/dataload"><state>Closed</state></jobInfo>'

# Get results

curl -H "X-SFDC-Session: your_session_id" \

https://your-instance.salesforce.com/services/async/47.0/job/job_id/batch/batch_id/result/result_id > contacts.csv

• Transfer your extracted Salesforce data directly into PostgreSQL using native database commands:

• Prepare your PostgreSQL table:

CREATE TABLE contacts (

    salesforce_id VARCHAR(18) PRIMARY KEY,

    name VARCHAR(255),

    email VARCHAR(255),

    phone VARCHAR(50),

    created_date TIMESTAMP DEFAULT CURRENT_TIMESTAMP

);

• Load the CSV data using COPY command:

COPY contacts(salesforce_id, name, email, phone)

FROM '/path/to/contacts.csv'

DELIMITER ','

CSV HEADER;

• Alternative: Use psql command for automated loading:

psql -h your_postgres_host -U your_username -d your_database \

-c "\COPY contacts(salesforce_id, name, email, phone) FROM 'contacts.csv' DELIMITER ',' CSV HEADER;"

Your Salesforce data is now successfully loaded into PostgreSQL!

Limitations of using Custom ETL Scripts

• As evident from the above steps, loading data through the manual method contains many steps that could be overwhelming if you are looking to do this regularly. You would need to configure additional scripts in case you need to bring data into real-time. 
• This method is unsuitable for bulk data movement, leading to slow performance, especially for large datasets.
• It is time-consuming and requires prior knowledge of coding, understanding APIs and configuring data mapping. 

What Type of Data Can You Export From Salesforce?

• Standard & Custom Object Data – Leads, Accounts, Contacts, Opportunities, Cases, and Custom Objects.
• Metadata & Configuration Data – Users, Roles, Profiles, Permission Sets, Workflow Rules, and Apex Triggers.
• Audit & Log Data – Login History, Field History Tracking, and Event Logs.
• Reports & Dashboards – Custom Reports and Dashboard Components.
• Files & Attachments – Documents, Notes, and Email Logs.

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Conclusion

Getting Salesforce data into PostgreSQL does not have to be a recurring engineering task. The right method depends on how much control your team needs and how frequently data needs to sync.

Custom ETL scripts offer full flexibility but come with ongoing maintenance, manual schema handling, and Salesforce API rate limit management that compounds as data volumes grow. For teams that want a faster, more reliable path, Hevo delivers on three things that matter most.

It is reliable. Fault-tolerant pipelines auto-heal from failures and adapt to schema changes without breaking. It is simple. Connect Salesforce to PostgreSQL in minutes through a guided no-code interface with zero infrastructure to manage. And it is transparent. Real-time dashboards and data pipeline health monitoring give your team complete visibility into every data sync, so nothing gets missed.

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Frequently Asked Questions (FAQs)

Vivek Sinha Former Director of Product Management, Hevo Data

Vivek Sinha has extensive experience in real-time analytics and cloud-native technologies. With a focus on Apache Pinot, he was a driving force in shaping innovation and defensible differentiators, including enhanced query processing, data mutability support, and cost-effective tiered storage solutions at Hevo. He also demonstrates a passion for exploring and implementing innovative trends within the dynamic data industry landscape.