Why HubSpot And PostgreSQL Integration Matters

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.

Why PostgreSQL HubSpot CRM Integration Matters in 2025

Key business benefits:

• Centralized access → unify CRM and internal databases for consistent reporting.
• Advanced analytics → leverage PostgreSQL queries for deeper insights.
• Operational efficiency → cut manual exports and reduce errors.
• Full customer view → combine HubSpot CRM data with product usage or financial data.

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.

3 Proven Methods for PostgreSQL HubSpot CRM Integration

There are three main ways to connect HubSpot with PostgreSQL, each with different technical requirements:

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In 2025, Stacksync stands out by offering real-time, bi-directional sync with sub-second latency, something tools like Fivetran or Zapier can’t fully deliver (Fivetran itself clarifies it focuses on ELT pipelines into a destination, not bi-directional sync

1. Manual CSV Exports And Imports

The simplest method involves exporting data files from HubSpot and importing them into PostgreSQL.

To export from HubSpot:

1. Navigate to the contacts, companies, or deals section
2. Click "Export" and select CSV format
3. Save the file to your computer

To import into PostgreSQL, use the COPY command (explained in the PostgreSQL COPY documentation)

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.

2. Custom Code And API Scripts

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.

3. No-Code Platforms And ETL Tools

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.

Resolving Update Conflicts

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.

How to Handle Conflicts in PostgreSQL HubSpot CRM Integration

• Last-write-wins: Fast but risky—can overwrite critical updates.
• System-priority: Make HubSpot the “source of truth” for CRM data, while PostgreSQL dominates for financial or product usage data.
• Field-level rules: Best practice in 2025. Define rules per property (e.g., HubSpot wins for contacts, PostgreSQL wins for invoices).

Document rules clearly to avoid confusion across teams.

Whatever strategy you choose, document it clearly so everyone knows which system to update for specific types of data.

Security And Data Integrity Best Practices

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

Common Pitfalls And Solutions

Many organizations encounter similar challenges when setting up HubSpot to PostgreSQL syncs.

Duplicate Record Handling

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.

Schema Changes

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.

API Rate Limits

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