Many companies use HubSpot as their CRM to manage contacts, companies, deals, and marketing activity. Others use PostgreSQL as a central database for business operations, analytics, or application development.

As data grows across platforms, keeping information consistent between systems becomes more important. This is where the concept of two way sync applies—allowing changes in either system to reflect in the other automatically.

This guide explains how syncing HubSpot with PostgreSQL works in 2025. It covers key approaches, setup steps, sync patterns, and best practices for accuracy, security, and performance.

Why Sync HubSpot And PostgreSQL

HubSpot excels at customer relationship management but has limitations for complex data analysis. PostgreSQL, as a relational database, offers powerful querying capabilities that complement HubSpot's strengths. When these systems remain disconnected, organizations face several challenges:

• Data becomes fragmented across platforms

• Teams work with outdated or inconsistent information

• Reporting requires manual exports and reconciliation

• Customer insights remain isolated from operational data

A two-way sync between HubSpot and PostgreSQL creates a unified data environment where both systems contain current, accurate information.

Benefits of connected systems:

• Enhanced analytics: Combine CRM data with financial, product, and operational metrics for comprehensive business intelligence

• Developer access: Enable technical teams to build custom applications using familiar database tools

• Data governance: Implement consistent backup, security, and compliance practices across all customer data

Understanding Two Way Sync

Two way sync (also called bidirectional synchronization) means data flows in both directions between systems. When information changes in either HubSpot or PostgreSQL, the update appears in the other system automatically.

Unlike one-way data pipelines that only move information in a single direction, two-way sync creates a continuous data loop. This approach maintains consistency across platforms without manual intervention.

For example, when a sales representative updates a contact's phone number in HubSpot, that change appears in PostgreSQL. Similarly, when a customer service application connected to PostgreSQL records a support interaction, that information updates the corresponding HubSpot record.

The technical components that enable effective two-way sync include:

• Change detection: Methods for identifying when data has been modified

• Field mapping: Rules that connect fields between different systems

• Conflict resolution: Logic for handling simultaneous updates to the same record

• Error handling: Processes for managing failed syncs and data inconsistencies

Key Approaches For HubSpot–PostgreSQL Integration

Organizations can connect HubSpot with PostgreSQL using several methods, each with different capabilities and requirements:

Manual Export/Import

This basic approach involves exporting CSV files from HubSpot and importing them into PostgreSQL using SQL commands. While simple, this method:

• Requires human intervention for each data transfer

• Creates only point-in-time snapshots rather than ongoing synchronization

• Cannot support real-time updates or two-way data flow

• Becomes impractical as data volume or update frequency increases

Custom API Integration

Developers can build custom code that connects to HubSpot's API and writes data to PostgreSQL. This approach:

• Offers complete flexibility in how data moves between systems

• Can support real-time updates and two-way sync with proper design

• Requires significant development resources and ongoing maintenance

• Demands expertise in both HubSpot's API and PostgreSQL

ETL/iPaaS Platforms

Integration platforms provide pre-built connectors for moving data between systems. These tools:

• Offer visual interfaces for mapping fields without extensive coding

• Support scheduled syncs at regular intervals

• May have limited support for real-time or two-way synchronization

• Vary widely in pricing, capabilities, and ease of use

Specialized Sync Tools

Purpose-built synchronization tools focus specifically on keeping data consistent across systems. These solutions:

• Support real-time, bidirectional data flow

• Handle conflict resolution automatically

• Adapt to schema changes without breaking

• Require minimal technical configuration

This comparison highlights key differences between approaches:

Steps To Configure Your First Sync

Setting up a basic sync between HubSpot and PostgreSQL involves five main steps:

1. Authorize HubSpot Access

Begin by creating API credentials in HubSpot:

1. Navigate to Settings > Integrations > Private Apps

2. Create a new private app with a descriptive name

3. Select the specific data access scopes needed (contacts, companies, deals)

4. Generate and securely store the access token

Remember that access tokens contain sensitive permissions and should be protected like passwords. Store them in secure environment variables or a secrets manager rather than in code repositories.

2. Set Up PostgreSQL Connection

Prepare your database to receive HubSpot data:

CREATE TABLE hubspot_contacts (
  id BIGINT PRIMARY KEY,
  firstname TEXT,
  lastname TEXT,
  email TEXT,
  created_at TIMESTAMPTZ,
  updated_at TIMESTAMPTZ
);

Create a dedicated database user with appropriate permissions for the integration. This user should have only the access levels required for the sync process, following the principle of least privilege.

3. Map Data Fields

Create a clear mapping between HubSpot properties and PostgreSQL columns. Consider data types carefully—HubSpot's fields may not perfectly match PostgreSQL's available types.

Common mapping challenges:

• Date formats: HubSpot uses ISO 8601 format while PostgreSQL has specific date/time types

• Custom fields: Properties created in HubSpot need corresponding columns in PostgreSQL

• Enumerated values: Dropdown fields in HubSpot may need validation or transformation

• Required fields: Some fields mandatory in one system may be optional in the other

Document your field mapping thoroughly, as it forms the foundation of your sync process.

4. Test And Verify Data Sync

Start with a small data sample to confirm your setup works correctly:

1. Sync a limited set of records (perhaps 10-20 contacts)

2. Verify the data appears correctly in PostgreSQL

3. Make changes in both systems to test bidirectional flow

4. Check for any missing fields or data type issues

Examine logs for warnings or errors that might indicate configuration problems.

5. Automate Scheduling

Once testing confirms your sync works properly, establish a regular schedule:

• For smaller datasets, full syncs might run hourly or daily

• For larger volumes, use incremental syncs based on "last modified" timestamps

• Consider business hours and usage patterns when scheduling updates

• Monitor performance metrics to adjust timing as needed

Best Practices For Secure And Scalable Data Transfers

Implementing a reliable sync between HubSpot and PostgreSQL requires attention to security, performance, and maintenance:

Security considerations:

• Encryption: Use TLS/SSL for all connections between systems

• Access controls: Apply the principle of least privilege to all integration accounts

• Audit logging: Track all data changes for compliance and troubleshooting

• Data classification: Identify and protect sensitive customer information

Performance optimization:

• Incremental syncs: Only process records that have changed since the last sync

• Batch processing: Group operations to reduce API calls and database overhead

• Connection pooling: Reuse database connections rather than creating new ones

• Indexing: Create appropriate indexes on frequently queried columns

Monitoring and maintenance:

• Review sync logs regularly for errors or warnings

• Track sync duration and record counts to identify trends

• Update field mappings when new properties are added in HubSpot

• Test the sync process after HubSpot or PostgreSQL updates

Common Challenges And Solutions

Even well-designed sync processes encounter obstacles. Here are frequent issues and their solutions:

API rate limiting: HubSpot restricts how many API requests you can make within a time period. To avoid hitting these limits:

• Implement backoff strategies that pause and retry when limits are reached

• Batch multiple records in single API calls where possible

• Schedule intensive sync operations during off-peak hours

Schema evolution: Both HubSpot and PostgreSQL schemas change over time as business needs evolve. Address this by:

• Building flexibility into your PostgreSQL schema (using JSONB fields for variable data)

• Implementing a schema comparison step before each sync

• Automating the addition of new columns when HubSpot properties are created

Data volume challenges: As records grow into the millions, sync performance can degrade. Mitigate this by:

• Partitioning PostgreSQL tables by date or other logical divisions

• Implementing parallel processing for large datasets

• Using timestamp filtering to process only recently changed records

Error recovery: When syncs fail, data can become inconsistent between systems. Protect against this with:

• Transaction-based operations that commit changes only when fully complete

• Detailed error logging that captures the specific records and fields affected

• Reconciliation processes that can detect and resolve inconsistencies

Moving Forward With Data Synchronization

Connecting HubSpot with PostgreSQL through two-way sync creates a more unified data environment. This integration bridges the gap between customer relationship management and data analytics, enabling more comprehensive insights and streamlined operations.

The approach you select depends on your technical resources, data volume, and real-time requirements. While manual exports might suffice for occasional analysis, automated sync tools provide continuous data consistency with minimal maintenance.

As your integration matures, consider expanding beyond basic contact synchronization to include companies, deals, tickets, and custom objects. This comprehensive approach creates a complete view of customer data across all systems.

For organizations managing large datasets or requiring real-time synchronization, specialized tools like Stacksync offer purpose-built solutions. These platforms handle the technical complexities of two-way sync while providing the security and reliability needed for production environments.

Ready to implement a professional HubSpot–PostgreSQL integration? Talk with a cloud architect to design a reliable, secure, and scalable solution tailored to your specific business needs.

FAQs About Syncing HubSpot And PostgreSQL

How do I handle custom objects in HubSpot when syncing to PostgreSQL?

Custom objects require creating corresponding tables in PostgreSQL with appropriate foreign key relationships to maintain the same data structure found in HubSpot.

What methods can I use to transform HubSpot data before it reaches PostgreSQL?

Data transformation can occur through ETL tools with built-in mapping functions, PostgreSQL views or functions, or middleware code that processes the data during the sync pipeline.

How can I efficiently sync millions of HubSpot records to PostgreSQL daily?

Large-volume syncs require incremental processing based on modified timestamps, batch operations instead of individual record updates, and partitioned PostgreSQL tables for improved query performance.