/
Many organizations work with both customer relationship management (CRM) platforms and structured databases. These systems often hold overlapping or related data, but in different formats and locations. Keeping this data consistent across both systems can be difficult, especially as records grow and change frequently.
This article explains how to synchronize data between HubSpot and PostgreSQL. It focuses on establishing a reliable two-way sync, where data flows in both directions—between a CRM and a database—without losing accuracy or context.
The goal is to provide a complete framework for setting up and maintaining this type of integration. The article covers data structure, sync methods, conflict handling, and regulatory considerations.
HubSpot is a cloud-based CRM platform that helps businesses track and manage interactions across marketing, sales, and customer service. It stores data such as contacts, companies, deals, tickets, and custom objects that are accessible through its web interface and APIs.
PostgreSQL is an open-source relational database management system (RDBMS). It stores data in tables using structured formats and supports SQL for querying and managing records. PostgreSQL is commonly used in backend systems, analytics pipelines, and enterprise applications.
These systems often work together when data collected in HubSpot also needs to be stored, processed, or analyzed in PostgreSQL. For example, a sales team might track leads in HubSpot, while a data team runs reports using PostgreSQL.
Synchronizing HubSpot and PostgreSQL allows data to stay consistent across both platforms. When customer information is unified, teams can make decisions based on complete and current data.
The benefits of HubSpot to PostgreSQL integration include:
Single source of truth: Both systems reflect the same customer data, reducing inconsistencies between tools
Enhanced reporting: PostgreSQL enables deeper SQL-based analysis than what's available in HubSpot alone
Operational efficiency: Automated sync eliminates manual exports and imports
Custom applications: Developers can build tools using PostgreSQL data that includes HubSpot information
Two-way HubSpot synchronization means changes in either system update the other automatically. This bi-directional flow keeps both platforms in alignment without manual intervention.
Before Sync | After Sync |
|---|---|
Sales updates contact in HubSpot; database remains outdated | Updates in HubSpot automatically appear in PostgreSQL |
Marketing exports CSV files manually for reporting | Data is always available in PostgreSQL for reporting |
Customer data exists in separate silos | Unified view of customer data across systems |
There are three main approaches to integrate HubSpot and PostgreSQL. Each method offers different levels of automation, complexity, and maintenance requirements.
This basic method involves downloading data from HubSpot and uploading it to PostgreSQL.
The process works like this:
In HubSpot, navigate to Contacts, Companies, or other objects and use the Export option
Download the data as a CSV file
Import the file into PostgreSQL using the COPY command:
COPY hubspot_contacts
FROM '/path/to/contacts.csv'
DELIMITER ','
CSV HEADER;
This approach works for occasional data transfers or one-time migrations but doesn't support real-time updates or automation.
This method uses HubSpot's REST APIs to retrieve data and insert it into PostgreSQL using code. It offers more control and automation than manual exports.
A simple Python example:
import requests
import psycopg2
# Get data from HubSpot
token = 'your_hubspot_token'
headers = {'Authorization': f'Bearer {token}'}
response = requests.get('https://api.hubapi.com/crm/v3/objects/contacts', headers=headers)
contacts = response.json()['results']
# Insert into PostgreSQL
conn = psycopg2.connect("dbname=yourdb user=username")
cur = conn.cursor()
for contact in contacts:
cur.execute("INSERT INTO contacts (id, email) VALUES (%s, %s)",
(contact['id'], contact['properties']['email']))
conn.commit()
This approach can be scheduled to run automatically and supports custom logic for transforming data between systems.
ETL (Extract, Transform, Load) platforms automate the entire sync process without requiring custom code. These tools connect to both HubSpot and PostgreSQL using pre-built connectors.
Popular options include:
The setup typically involves:
Connecting to both systems using credentials
Mapping fields between HubSpot and PostgreSQL
Setting a sync schedule
Configuring error handling and notifications
ETL platforms offer the easiest implementation but may have less flexibility than custom code.
Each HubSpot object (Contacts, Companies, Deals) typically becomes a table in PostgreSQL. The fields from HubSpot become columns in these tables.
A basic mapping example:
HubSpot Field | PostgreSQL Column | Data Type |
|---|---|---|
id | hubspot_id | TEXT |
firstname | first_name | VARCHAR(255) |
VARCHAR(255) | ||
createdate | created_at | TIMESTAMP |
Custom fields in HubSpot can be added as additional columns in PostgreSQL. This mapping forms the foundation of your sync process.
Two-way sync can run at different intervals depending on how current the data needs to be:
Real-time sync: Updates happen within seconds of changes
Hourly sync: Batched updates run every hour
Daily sync: Updates process once per day
Real-time sync uses webhooks that trigger immediate updates when data changes. Scheduled syncs run at fixed intervals using cron jobs or platform schedulers.
When the same record changes in both systems before a sync occurs, conflict resolution rules determine which version to keep.
Common approaches include:
Timestamp-based: The most recently updated record wins
System priority: One system (usually HubSpot) is designated as the master for certain fields
Field-level rules: Different rules apply to different fields
Clear conflict resolution rules prevent data loss and ensure consistency across systems.
Real-time synchronization between HubSpot and PostgreSQL faces two main challenges: API rate limits and data conflicts.
HubSpot limits how many API calls you can make in a given time period. For most accounts, this is around 100 requests per 10 seconds. When syncing large datasets, you may hit these limits.
Strategies to work within rate limits include:
Batch processing: Group multiple records into single API calls
Incremental sync: Only process records that have changed since the last sync
Queuing: Place updates in a queue and process them gradually
Caching: Store frequently accessed data locally to reduce API calls
Data conflicts occur when the same record changes in both systems at nearly the same time. A robust sync system needs rules to handle these situations automatically.
For example, if a contact's email address changes in both HubSpot and PostgreSQL, the system might keep the most recently updated version or prioritize changes from a specific system.
Secure integration between HubSpot and PostgreSQL requires proper handling of authentication credentials.
For HubSpot, this typically means using API keys or OAuth tokens. These credentials grant access to the HubSpot API and should be stored securely, not in code or configuration files.
For PostgreSQL, database connection strings contain usernames, passwords, and host information. These should also be protected using environment variables or secret management tools.
Best practices include:
Rotating API keys periodically
Using the principle of least privilege (granting only necessary permissions)
Implementing SSL/TLS for database connections
When syncing customer data between systems, privacy regulations like GDPR may apply. Consider these practices:
Sync only the data fields necessary for business purposes
Implement data retention policies in both systems
Maintain audit logs of data access and modifications
Ensure personal data is encrypted during transfer
These measures help maintain compliance while enabling effective data integration.
Synchronizing HubSpot and PostgreSQL creates a powerful data foundation that supports both operational CRM needs and analytical capabilities. The right approach depends on your specific requirements, technical resources, and data volume.
For simple needs, manual exports or basic scripts may suffice. For ongoing, reliable synchronization, ETL platforms or custom integration solutions offer more robust options.
Key factors for success include:
Clear data mapping between systems
Well-defined conflict resolution rules
Appropriate sync frequency based on business needs
Monitoring and error handling
Stacksync provides a platform that enables bi-directional HubSpot and PostgreSQL sync without complex infrastructure. It supports real-time data sync with automatic conflict resolution and field mapping.
To explore how Stacksync supports two-way sync between HubSpot and PostgreSQL, talk with a cloud architect.
Two-way sync creates a bi-directional data flow where changes in either HubSpot or PostgreSQL automatically update the other system, keeping both platforms synchronized.
Yes, custom objects from HubSpot can be synchronized to PostgreSQL by mapping them to dedicated tables and establishing proper relationships through foreign keys.
Conflict resolution rules determine which version is kept. Options include timestamp-based decisions (newest wins), system priority rules, or field-level policies.
The optimal frequency depends on your business needs - real-time for critical operational data or daily batches for analytics purposes.
Secure synchronization uses encrypted connections (SSL/TLS), proper API authentication, secure credential storage, and data access controls.
