/
When two systems store important business data, connecting them helps reduce duplication, delays, and confusion. This guide explains how to synchronize HubSpot, a CRM platform, with PostgreSQL, a relational database.
Two-way sync is a method that allows data to move in both directions between systems. This means updates in one system appear in the other and vice versa, keeping records consistent.
This article focuses on how to set up and maintain a two-way sync between HubSpot and PostgreSQL in 2025. It covers methods, steps, best practices, and common issues involved in this type of integration.
HubSpot is a cloud-based customer relationship management (CRM) platform used to manage sales, marketing, and customer service activities. PostgreSQL is an open-source relational database used to store and query structured data.
Integrating HubSpot with PostgreSQL creates a shared data environment. This allows teams to access the same information across business systems without manual transfers or duplicate entries.
Key benefits:
Centralized Data Access: Combine marketing and sales data with internal databases for unified reporting
Enhanced Analytics: Perform advanced queries using PostgreSQL's powerful query capabilities
Operational Efficiency: Eliminate repetitive data entry and manual exports
For example, a software company might sync customer information from HubSpot to PostgreSQL to combine it with product usage data. This gives them a complete view of how customers interact with both sales teams and their product.
There are three main ways to connect HubSpot with PostgreSQL, each with different technical requirements:
Method | How It Works | Best For | Complexity |
|---|---|---|---|
Manual CSV | Export files from HubSpot, import to PostgreSQL | Occasional syncs, small teams | Low |
API Scripts | Custom code using HubSpot's API | Regular syncs, specific requirements | Medium |
ETL Tools | Pre-built connectors that automate the process | Frequent syncs, non-technical users | Low-Medium |
The simplest method involves exporting data files from HubSpot and importing them into PostgreSQL.
To export from HubSpot:
Navigate to the contacts, companies, or deals section
Click "Export" and select CSV format
Save the file to your computer
To import into PostgreSQL, use the COPY command:
COPY contacts FROM '/path/to/file.csv' DELIMITER ',' CSV HEADER;
This approach works for occasional updates but becomes time-consuming if done frequently. It also lacks automation, requiring someone to manually perform each export and import.
For more automated syncs, developers can write code that connects directly to HubSpot's API to retrieve data and insert it into PostgreSQL.
A simple Python example might look like:
import requests
import psycopg2
# Get data from HubSpot
headers = {"Authorization": "Bearer YOUR_TOKEN"}
response = requests.get("https://api.hubapi.com/crm/v3/objects/contacts", headers=headers)
contacts = response.json()["results"]
# Connect to PostgreSQL and insert data
conn = psycopg2.connect("dbname=mydatabase user=myuser")
cursor = conn.cursor()
for contact in contacts:
cursor.execute(
"INSERT INTO contacts (id, email, firstname) VALUES (%s, %s, %s)",
(contact["id"], contact["properties"]["email"], contact["properties"]["firstname"])
)
conn.commit()
This method requires programming skills but offers more control over what data syncs and when.
ETL (Extract, Transform, Load) tools provide ready-made connectors for both HubSpot and PostgreSQL. These tools handle the technical details of connecting systems, mapping fields, and scheduling regular updates.
Popular options include:
Stacksync
Fivetran
Airbyte
Zapier (for simpler syncs)
These platforms typically offer user-friendly interfaces where you can select which HubSpot objects to sync, map fields to PostgreSQL columns, and set up automatic sync schedules.
Two-way sync (bidirectional synchronization) means changes in either system update the other system automatically. This differs from one-way sync, where data flows in only one direction.
How two-way sync works:
When a record changes in HubSpot, the change is detected and applied to PostgreSQL
When the same record changes in PostgreSQL, the change is detected and applied back to HubSpot
Conflict resolution rules determine what happens when both systems change the same record
Setting up two-way sync requires:
A way to detect changes in both systems
Logic to resolve conflicts when they occur
A method to prevent endless update loops
For HubSpot and PostgreSQL, this typically involves:
Using HubSpot webhooks to detect CRM changes
Creating database triggers in PostgreSQL to detect database changes
Setting up a middle layer (ETL tool or custom code) to manage the synchronization
Setting up a sync between HubSpot and PostgreSQL involves several key steps:
Schema mapping means matching HubSpot fields to PostgreSQL columns. This tells the sync process which pieces of data correspond to each other.
For example, you might map:
HubSpot contact email → PostgreSQL contacts.email
HubSpot company name → PostgreSQL companies.name
HubSpot deal amount → PostgreSQL deals.amount
When creating this mapping, pay attention to data types. A date in HubSpot needs to map to a date type in PostgreSQL, not a text field.
To access HubSpot data programmatically, you'll need authentication credentials. HubSpot offers several options:
API Key: A simple string that grants access to your HubSpot account. Easy to set up but less secure for production use.
OAuth: A more secure protocol that grants specific permissions and can be revoked if needed. Better for production environments.
For PostgreSQL, you'll need:
Database username and password
Host address
Database name
Port number (usually 5432)
Always store these credentials securely, not in code files.
With mapping and authentication in place, the next step is moving the actual data. This happens in two main ways:
Full sync: Copies all data from source to destination. Good for initial setup but inefficient for ongoing updates.
Incremental sync: Only copies records that have changed since the last sync. More efficient but requires tracking what's changed.
For HubSpot to PostgreSQL, incremental sync typically uses:
The "updated_at" property in HubSpot to find recently changed records
Comparison of record IDs and timestamps to determine what needs updating
Even well-designed syncs encounter problems. Common issues include:
Network timeouts
Authentication failures
Schema mismatches
API rate limits
A robust sync process includes:
Detailed error logging
Automatic retry mechanisms
Notifications for critical failures
A way to resume from where it left off
When both systems can change the same data, conflicts inevitably arise. For example, a sales rep might update a contact's phone number in HubSpot while a database admin corrects the same field in PostgreSQL.
Common conflict resolution strategies include:
Last-write-wins: The most recent change takes precedence, regardless of which system it came from.
System priority: One system (usually HubSpot for CRM data) is designated as the "source of truth" and its changes always win.
Field-level rules: Different fields might have different rules. Contact details might prioritize HubSpot, while custom fields might prioritize PostgreSQL.
Whatever strategy you choose, document it clearly so everyone knows which system to update for specific types of data.
When syncing sensitive customer data between systems, security becomes paramount.
Key security considerations:
Encrypted Connections: Use SSL/TLS for all data transfers
Minimal Access: Grant only the permissions needed for the sync to work
Credential Management: Store API keys and passwords in secure vaults, not in code
Audit Trails: Log who changed what and when in both systems
For data integrity, implement these safeguards:
Validate data before writing to either system
Use database constraints in PostgreSQL to prevent invalid data
Implement checksums or record counts to verify complete transfers
Back up both systems regularly
Many organizations encounter similar challenges when setting up HubSpot to PostgreSQL syncs.
Problem: The same contact appears multiple times in either system.
Solution: Establish a unique identifier (usually email for contacts, domain for companies) and use "upsert" operations (update if exists, insert if not) rather than always inserting.
Problem: Adding custom properties in HubSpot or columns in PostgreSQL breaks the sync.
Solution: Design your sync to detect schema changes and either adapt automatically or notify administrators. Make schema changes in a controlled manner, updating the sync configuration accordingly.
Problem: HubSpot limits how many API calls you can make per day.
Solution: Implement these strategies to work within limits:
Batch requests where possible
Space out sync operations
Prioritize important data for more frequent syncs
Use webhooks for real-time updates of critical changes
Successful HubSpot to PostgreSQL synchronization depends on thoughtful planning and implementation. The most effective integrations:
Start with clear business requirements about what data needs to sync and why
Choose the right sync method based on technical resources and update frequency
Map fields carefully, considering data types and relationships
Implement proper error handling and monitoring
Establish clear rules for conflict resolution
Tools like Stacksync can simplify this process by providing ready-made connectors and handling the technical complexities of maintaining a reliable two-way sync.
For organizations looking to unify their customer data across platforms, a well-implemented HubSpot to PostgreSQL sync creates a foundation for better reporting, more informed decision-making, and smoother operations.
Synchronization frequency depends on how quickly you need updated data and your API limits. Most organizations sync contact and company data several times per day, while high-volume or time-sensitive data might sync hourly or in near-real-time using webhooks.
When your PostgreSQL schema changes (adding, removing, or modifying columns), you'll need to update your sync configuration to match. Without updates, new fields won't sync, and removed fields may cause errors. Most ETL tools allow you to modify field mappings without starting over.
Yes, most sync solutions allow filtering to synchronize only specific records. You can filter based on HubSpot properties like record creation date, lifecycle stage, or any custom property. This helps manage data volume and focus on the most relevant records for your database.
