Connecting systems like HubSpot and PostgreSQL allows data to move between marketing, sales, and operations in a consistent and structured way. This article explains how to set up that connection, focusing on the technical architecture behind the integration.

The process involves using HubSpot's API to extract CRM data, transforming it to match a PostgreSQL schema, and loading it into a relational database. With the right configuration, this sync can be made bi-directional—allowing updates in PostgreSQL to reflect back in HubSpot.

The following sections cover the key components of this setup, including API access, schema design, data transformation, and automation strategies for maintaining sync over time.

Why Integrate HubSpot With PostgreSQL

HubSpot stores customer relationship data, such as contacts, companies, deals, and engagement history. PostgreSQL is often used for reporting, analytics, and storing operational data. Connecting these two systems allows organizations to combine customer insights with business operations in a single environment.

This integration supports use cases like building dashboards, tracking sales performance, or running predictive models using centralized data. By syncing HubSpot data into PostgreSQL, teams can query structured CRM data alongside other business data sources.

Two-way sync enables scenarios where updates in PostgreSQL—such as a change in customer status or support ticket resolution—can flow back into HubSpot automatically. This helps align marketing and sales with real-time operational context.

![Diagram showing data flow between HubSpot and PostgreSQL]

Key Methods For Connecting HubSpot And PostgreSQL

There are three primary methods for integrating HubSpot with PostgreSQL, each with different technical requirements and use cases.

1. Manual CSV Export And Import

The simplest approach involves exporting CSV files from HubSpot and importing them into PostgreSQL. This method works well for occasional or one-time data transfers.

• Process: Export data from HubSpot as CSV → Create matching table in PostgreSQL → Import using COPY command

• Best for: Small datasets, infrequent updates, or initial data loading

• Limitations: No automation, potential for human error, quickly becomes outdated

2. Custom Scripting With HubSpot API

For more control and automation, custom scripts can pull data from HubSpot's API and insert it into PostgreSQL. This method requires programming knowledge but offers flexibility.

A basic Python example:

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"]

# Insert into PostgreSQL
conn = psycopg2.connect("dbname=mydb user=user password=pass")
cursor = conn.cursor()
for contact in contacts:
    cursor.execute(
        "INSERT INTO contacts (id, email, name) VALUES (%s, %s, %s)",
        (contact["id"], contact["properties"]["email"], contact["properties"]["name"])
    )
conn.commit()

3. Integration Platforms

Integration platforms provide pre-built connectors for HubSpot and PostgreSQL, allowing setup through a visual interface rather than code.

These platforms handle authentication, data mapping, and error handling automatically, making them accessible to teams without extensive development resources.

Understanding Two-Way Sync Between Systems

Two-way sync (also called bidirectional synchronization) means data can flow in both directions between HubSpot and PostgreSQL. When a record changes in either system, the change is reflected in the other system.

This differs from one-way sync, where data only flows from a source to a destination without updates returning to the source. Two-way sync creates a more dynamic relationship between systems.

For example, with two-way sync:

• A sales rep updates a contact's phone number in HubSpot → The phone number is updated in PostgreSQL

• An automated process updates a deal status in PostgreSQL → The deal status is updated in HubSpot

The benefits of two-way sync include:

• Data consistency: Information stays the same across all systems

• Workflow flexibility: Teams can work in their preferred system

• Process automation: Updates trigger actions in connected systems

Two-way sync requires careful planning to handle conflicts when the same record is changed in both systems simultaneously. Most implementations use timestamps or priority rules to determine which change takes precedence.

HubSpot API Authentication And Data Access

Accessing HubSpot's API requires proper authentication. The most common method is using a private app access token, which provides secure access to specific data without requiring user login.

To create a token:

1. Go to HubSpot settings → Integrations → Private Apps

2. Create a new private app with the necessary scopes (permissions)

3. Copy the generated access token

This token is included in the Authorization header of API requests:

Authorization: Bearer YOUR_ACCESS_TOKEN

HubSpot's API is organized by object types, with endpoints for contacts, companies, deals, and more. Each endpoint returns data in JSON format and supports filtering, sorting, and pagination.

Common endpoints include:

• /crm/v3/objects/contacts - Access contact records

• /crm/v3/objects/deals - Access deal records

• /crm/v3/objects/companies - Access company records

When making requests, be mindful of rate limits. HubSpot restricts the number of API calls per day based on your subscription level. Using pagination and batching requests helps stay within these limits.

Preparing PostgreSQL For HubSpot Data

Before importing data, PostgreSQL needs tables that match HubSpot's data structure. Each HubSpot object type typically corresponds to a separate table.

A basic contacts table might look like:

CREATE TABLE hubspot_contacts (
  id SERIAL PRIMARY KEY,
  hubspot_id VARCHAR(255) UNIQUE,
  email VARCHAR(255),
  firstname VARCHAR(100),
  lastname VARCHAR(100),
  phone VARCHAR(50),
  created_at TIMESTAMP,
  updated_at TIMESTAMP
);

HubSpot allows custom properties, which can be handled in two ways:

1. Add columns for each custom property:

   ALTER TABLE hubspot_contacts 
   ADD COLUMN customer_tier VARCHAR(50);
   

2. Use a JSONB column for all custom properties:

   ALTER TABLE hubspot_contacts
   ADD COLUMN custom_properties JSONB;
   

The first approach makes querying easier but requires schema changes when new properties are added. The second approach is more flexible but makes queries slightly more complex.

Indexes improve query performance, especially for columns used in WHERE clauses or joins:

CREATE INDEX idx_hubspot_contacts_email ON hubspot_contacts(email);
CREATE INDEX idx_hubspot_contacts_updated_at ON hubspot_contacts(updated_at);

Implementing Two-Way Sync Workflow

A complete two-way sync implementation involves several components working together:

1. Data extraction from HubSpot using the API

2. Data transformation to match PostgreSQL's schema

3. Data loading into PostgreSQL tables

4. Change tracking to identify updates in both systems

5. Conflict resolution when records are updated in both places

For extracting data, pagination handles large datasets:

url = "https://api.hubapi.com/crm/v3/objects/contacts"
params = {"limit": 100}
all_contacts = []

while url:
    response = requests.get(url, headers=headers, params=params)
    data = response.json()
    all_contacts.extend(data["results"])
    
    # Get URL for next page if it exists
    next_page = data.get("paging", {}).get("next", {}).get("link")
    url = next_page if next_page else None

For loading data, "upsert" operations update existing records or insert new ones:

INSERT INTO hubspot_contacts (hubspot_id, email, firstname, lastname)
VALUES ('123', 'john@example.com', 'John', 'Smith')
ON CONFLICT (hubspot_id) 
DO UPDATE SET email = EXCLUDED.email, 
              firstname = EXCLUDED.firstname,
              lastname = EXCLUDED.lastname;

For two-way sync, track changes in PostgreSQL using timestamps or triggers:

CREATE OR REPLACE FUNCTION update_timestamp()
RETURNS TRIGGER AS $$
BEGIN
    NEW.updated_at = NOW();
    RETURN NEW;
END;
$$ LANGUAGE plpgsql;

CREATE TRIGGER update_contacts_timestamp
BEFORE UPDATE ON hubspot_contacts
FOR EACH ROW EXECUTE FUNCTION update_timestamp();

This trigger records when each record was last updated, making it possible to identify changes that need to be sent back to HubSpot.

Handling Sync Conflicts And Data Integrity

When implementing two-way sync, conflicts occur when the same record is modified in both systems before synchronization happens. There are several strategies to handle these conflicts:

• Last-write-wins: The most recent change takes precedence

• Source priority: Changes in one system always override the other

• Merge fields: Combine non-conflicting field changes from both systems

• Manual resolution: Flag conflicts for human review

Most implementations use timestamps to determine which change is newer:

# Pseudocode for conflict resolution
if hubspot_updated_at > postgres_updated_at:
    # HubSpot change is newer, update PostgreSQL
    update_postgres_record(hubspot_data)
elif postgres_updated_at > hubspot_updated_at:
    # PostgreSQL change is newer, update HubSpot
    update_hubspot_record(postgres_data)
else:
    # Same timestamp or can't determine, use priority rule
    if priority_system == "hubspot":
        update_postgres_record(hubspot_data)
    else:
        update_hubspot_record(postgres_data)

Data integrity is maintained through:

• Unique identifiers: Using HubSpot IDs as primary keys

• Transactions: Wrapping database operations in transactions

• Validation: Checking data types and constraints before updates

• Logging: Recording all sync operations for troubleshooting

Automating And Monitoring The Integration

Once the sync logic is implemented, automation keeps the systems in sync without manual intervention. There are two main approaches:

Scheduled Synchronization

A program runs at regular intervals to check for changes and sync them between systems. This can be implemented using cron jobs, scheduled tasks, or workflow tools.

Example cron entry to run sync every 15 minutes:

*/15 * * * * /path/to/sync_script.py

Real-time Synchronization

HubSpot webhooks notify your system immediately when data changes. This approach provides lower latency but requires more infrastructure.

To set up webhooks:

1. Create an endpoint in your application to receive webhook events

2. Register the endpoint URL in HubSpot's settings

3. Process incoming events to trigger sync operations

Monitoring is essential to ensure the integration works correctly over time. Key metrics to track include:

• Number of records synced

• Sync success/failure rates

• API rate limit usage

• Sync latency (time between change and sync)

• Number of conflicts detected

Alerts can notify administrators when issues occur, such as failed syncs or approaching rate limits.

Streamline Your Database Integration With Stacksync

Stacksync simplifies the process of connecting HubSpot with PostgreSQL through a specialized platform for database integration. The system handles the technical aspects of two-way sync without requiring custom code development.

Key features include:

• Pre-built connectors for HubSpot and PostgreSQL

• Visual field mapping interface

• Automated schema management

• Conflict resolution rules

• Real-time or scheduled sync options

The platform is designed for data-intensive environments where maintaining consistency between systems is critical. By abstracting the complexity of API integration, data transformation, and conflict management, it allows teams to focus on using the data rather than maintaining the connection between systems.

For organizations looking to implement HubSpot-PostgreSQL integration, Stacksync offers a streamlined approach that reduces technical overhead while providing enterprise-grade reliability.

Frequently Asked Questions About HubSpot And PostgreSQL

How do I handle HubSpot API version changes in my PostgreSQL integration?

Monitor HubSpot's developer changelog for API updates and implement version checking in your integration code to detect and adapt to changes automatically.

What is the most efficient way to sync only updated HubSpot records to PostgreSQL?

Use HubSpot's updated_at property to filter API requests, retrieving only records modified since your last sync to minimize data transfer and processing time.

How can I maintain referential integrity between HubSpot objects in PostgreSQL?

Create foreign key relationships in your PostgreSQL schema that mirror the associations in HubSpot, such as linking contacts to companies using the HubSpot IDs as references.

What PostgreSQL extensions are helpful when working with HubSpot data?

The jsonb_ops extension helps when storing and querying JSON data from HubSpot, while pg_cron can be useful for scheduling regular synchronization tasks.