/
In 2025, many businesses work with both HubSpot and PostgreSQL. HubSpot is a customer relationship management (CRM) platform used to track leads, sales, and marketing activity. PostgreSQL is a relational database used to store and manage structured business data.
These systems often hold related information. For example, HubSpot might track a customer's sales interactions, while PostgreSQL stores order history or billing data. Without a connection between the two, teams may work with incomplete or outdated information.
Syncing HubSpot and PostgreSQL allows both systems to stay updated with the same data. This means a change in one system shows up in the other, reducing gaps or delays in information. This type of connection is called a "two-way sync."
Two-way sync is useful when multiple teams or tools rely on different systems but work with the same data. It helps ensure consistency between what users see in HubSpot and what is stored in PostgreSQL.
Two-way sync keeps data consistent between HubSpot and PostgreSQL. When someone updates a contact in HubSpot, that change appears in PostgreSQL. When data changes in PostgreSQL, those updates flow back to HubSpot. This happens automatically without manual intervention.
This integration connects customer-facing tools with backend systems. Marketing teams using HubSpot can see the same information as engineering teams using PostgreSQL. Both groups work with accurate, current data.
Common applications include:
Combining contact data with product usage metrics for customer health scoring
Creating reports that merge marketing engagement with revenue data
Automating lead qualification by syncing enriched data between systems
The sync also supports internal workflows. When a sales rep changes a customer's status in HubSpot, that update can trigger changes in systems connected to PostgreSQL, reducing manual data entry.
Three main approaches exist for connecting HubSpot and PostgreSQL: manual transfers, custom scripts, and specialized tools. Each method suits different technical requirements and data volumes.
This basic method involves exporting data from HubSpot as a CSV file, then importing it into PostgreSQL. In HubSpot, navigate to the desired object (like Contacts), select "Export" from the Actions menu, and download the CSV file. Then use PostgreSQL's COPY command or pgAdmin to import the data.
Best for: One-time migrations or infrequent updates of small datasets
Limitations: Time-consuming, error-prone, and lacks automation
Technical requirements: Basic knowledge of both platforms, no coding needed
Custom scripts automate the sync process using programming languages like Python or Node.js. These scripts connect to HubSpot's API, retrieve data, transform it to match PostgreSQL's structure, and insert or update records using SQL commands.
A simple Python script might:
Connect to HubSpot using API credentials
Request contact data with specific fields
Process the JSON response
Connect to PostgreSQL
Insert or update records based on unique identifiers
This approach requires programming knowledge but offers flexibility for custom business logic and scheduling.
ETL (Extract, Transform, Load) tools and no-code connectors provide user interfaces for setting up and managing syncs without writing code. These platforms handle authentication, field mapping, scheduling, and error handling.
Popular tools offer features like:
Visual field mapping between systems
Conflict resolution settings
Scheduled or real-time sync options
Monitoring and error alerts
This method balances ease of use with powerful capabilities for ongoing, automated synchronization.
Two-way sync, also called bidirectional synchronization, means changes flow in both directions between systems. This differs from one-way sync where data only moves from a source to a destination.
In a two-way sync between HubSpot and PostgreSQL:
Updates in HubSpot appear in PostgreSQL
Updates in PostgreSQL appear in HubSpot
The process happens automatically based on triggers or schedules
This approach creates a unified data environment where both systems contain matching information. When a field changes in either system, the update propagates to maintain consistency.
Two-way sync requires careful planning to avoid update loops or conflicts. If both systems change the same record simultaneously, the sync process must decide which version to keep. This is handled through conflict resolution rules like timestamp comparison or designating a primary system.
The benefits of two-way sync include:
Data consistency: Teams using either system see the same information
Workflow automation: Updates trigger appropriate actions in connected systems
Reduced manual effort: Eliminates duplicate data entry and copy-paste tasks
Schema mapping aligns fields between HubSpot and PostgreSQL to ensure data transfers correctly. This process matches each HubSpot property with its corresponding PostgreSQL column.
Start by identifying which HubSpot objects to sync (contacts, companies, deals) and create matching tables in PostgreSQL. Each table needs columns for all relevant HubSpot properties. For example, the contacts table might include columns for email, first name, last name, and lead status.
Data types often differ between systems. HubSpot uses string-based formats while PostgreSQL has structured types:
HubSpot text fields → PostgreSQL VARCHAR or TEXT
HubSpot dates → PostgreSQL TIMESTAMP
HubSpot numbers → PostgreSQL INTEGER or DECIMAL
Custom fields in HubSpot need special attention. These user-defined properties vary by account and require corresponding columns in PostgreSQL. When HubSpot field names contain spaces or special characters, rename them during mapping to follow PostgreSQL's naming rules.
Key mapping considerations include:
Primary keys: Identify unique identifiers (like email address for contacts) to match records across systems
Required fields: Ensure all mandatory fields have values to prevent sync errors
Field length: Set appropriate column sizes in PostgreSQL to accommodate HubSpot data
Real-time sync updates data immediately after changes occur, rather than waiting for scheduled batches. This approach keeps both systems current with minimal delay.
HubSpot supports webhooks, which are automated notifications sent when records change. When someone updates a contact in HubSpot, a webhook can trigger an immediate update in PostgreSQL. Similarly, database triggers in PostgreSQL can detect changes and initiate updates to HubSpot.
Implementing real-time sync requires:
Setting up HubSpot webhooks for relevant objects
Creating an endpoint to receive webhook data
Processing the data and updating PostgreSQL
Configuring PostgreSQL triggers or change tracking
Building logic to send PostgreSQL changes to HubSpot's API
Real-time sync offers advantages for time-sensitive operations but increases system complexity. It requires robust error handling and monitoring to ensure reliability.
For many use cases, near-real-time sync (updating every few minutes) provides similar benefits with less complexity. This approach uses scheduled jobs that run frequently rather than event-based triggers.
Security and reliability form the foundation of effective data synchronization. When connecting HubSpot and PostgreSQL, several practices help protect sensitive information and ensure consistent operation.
Customer data often contains personal information subject to regulations like GDPR or CCPA. A secure sync implementation includes:
Encrypted connections for all data transfers
Secure storage of API credentials and access tokens
Role-based access controls for both systems
Data masking for sensitive fields when appropriate
Audit logs to track who accessed or modified data
Sync processes face various challenges including network issues, API limits, and data validation errors. Robust error handling includes:
Rate limit management: HubSpot restricts API calls to prevent overuse. Implement backoff strategies that pause and retry when limits are reached.
Validation checks: Verify data formats before sending to prevent rejection due to invalid values.
Transaction handling: Use database transactions in PostgreSQL to ensure updates either complete fully or roll back entirely.
Logging and alerts: Record all sync activities and errors, with notifications for critical failures.
Regular monitoring helps identify and resolve issues before they impact business operations. Check sync logs daily and set up automated alerts for unusual patterns or failures.
A well-implemented sync between HubSpot and PostgreSQL creates a unified view of business data. This integration supports both operational efficiency and strategic decision-making by ensuring all teams work with consistent information.
The right approach depends on specific business needs, technical resources, and data volumes. Small organizations with basic requirements might start with scheduled batch syncs, while enterprises with complex workflows may implement real-time, bidirectional synchronization.
Stacksync's platform offers no-code, bidirectional sync capabilities that simplify this process. The system handles field mapping, conflict resolution, and security without requiring custom development or infrastructure management.
For organizations seeking a robust HubSpot-PostgreSQL integration, talk with a Cloud Architect at Stacksync to learn about real-time, two-way sync options with enterprise-grade security.
Setup time ranges from a few hours to several days, depending on the number of objects being synced, the method used, and the complexity of field mapping.
The primary HubSpot objects available for sync include contacts, companies, deals, tickets, products, and custom objects. These are accessible through the HubSpot API.
Data consistency relies on conflict resolution strategies such as timestamp comparison or source-of-truth designation, combined with regular reconciliation processes to identify and correct mismatches.
Key security considerations include encrypting data transfers, securing API credentials, implementing access controls, and following relevant compliance standards like GDPR and CCPA.
Yes, historical data can be synced by performing an initial full export from HubSpot before starting ongoing incremental syncs, providing a complete dataset at the beginning of the integration.
