Destinations

Destinations

Destinations are where your standardized data goes. Outrun takes the clean, standardized objects from your sources and delivers them to your chosen destinations, enabling powerful bi-directional sync scenarios.

How Destinations Work

When you configure a destination in Outrun:

  1. Data Reception - Standardized objects (People, Organizations, Relationships) arrive from sources
  2. Field Mapping - Outrun maps standardized fields to destination-specific fields
  3. Validation - Data is validated against destination requirements and constraints
  4. Delivery - Clean data is written to your destination system via APIs

Supported Destinations

We currently support 2 destination systems that also function as sources:

Bi-Directional Sync

All our destination systems also function as sources, enabling powerful bi-directional sync scenarios:

Two-Way Sync

Configure the same system as both source and destination for true bi-directional synchronization.

  • • Changes in either system sync to the other
  • • Conflict resolution and deduplication
  • • Maintains data consistency across platforms

Multi-System Sync

Use multiple sources feeding into multiple destinations for comprehensive data distribution.

  • • Central data hub with multiple endpoints
  • • Standardized data across all systems
  • • Single source of truth maintenance

Destination Capabilities

Field Mapping

  • Automatic Mapping: Smart defaults for common field mappings
  • Custom Mapping: Configure specific field transformations
  • Required Fields: Automatic validation of destination requirements
  • Data Types: Proper type conversion and validation

Data Validation

  • Schema Validation: Ensure data meets destination requirements
  • Constraint Checking: Validate against picklists, formats, and rules
  • Error Handling: Graceful handling of validation failures
  • Retry Logic: Automatic retry for transient failures

Performance Optimization

  • Batch Processing: Efficient bulk operations where supported
  • Rate Limiting: Respect destination API limits
  • Incremental Updates: Only send changed data
  • Conflict Resolution: Handle duplicate and conflicting data

Common Use Cases

CRM Synchronization

HubSpot (Source) → Outrun → Zoho CRM (Destination)

Keep your CRM systems in sync with standardized contact and company data.

Data Consolidation

Multiple Sources → Outrun → Single CRM (Destination)

Consolidate data from multiple systems into a single CRM for unified management.

Backup and Migration

Primary CRM (Source) → Outrun → Backup CRM (Destination)

Maintain backup systems or migrate between CRM platforms.

Multi-Regional Sync

Regional CRM (Source) → Outrun → Global CRM (Destination)

Sync regional data to global systems while maintaining local operations.

Rate Limiting & Performance

Each destination has specific rate limits that Outrun respects:

  • HubSpot: 10 requests per second for destination writes
  • Zoho CRM: 3 requests per 10 seconds for write operations

Performance Optimization

Outrun automatically optimizes destination writes with intelligent batching, retry logic, and rate limit management to ensure reliable data delivery.

Data Quality & Validation

Required Fields

Each destination has specific required fields that must be populated:

  • HubSpot: Email (People), Company Name (Organizations)
  • Zoho CRM: Last Name (People), Account Name (Organizations)

Data Transformation

  • Field Mapping: Automatic mapping between standardized and native fields
  • Type Conversion: Proper data type handling (strings, numbers, dates)
  • Format Validation: Email, phone, URL format validation
  • Constraint Checking: Picklist values, field length limits

Error Handling

  • Validation Errors: Clear reporting of field validation failures
  • Retry Logic: Automatic retry for transient API failures
  • Conflict Resolution: Handle duplicate records and data conflicts
  • Monitoring: Real-time sync status and error reporting

Best Practices

Setup Recommendations

  1. Authentication: Use dedicated service accounts for destinations
  2. Field Mapping: Review and customize field mappings for your use case
  3. Required Fields: Ensure source data includes all required destination fields
  4. Testing: Start with small data sets to verify mappings and behavior

Performance Optimization

  1. Batch Size: Configure appropriate batch sizes for your data volume
  2. Sync Frequency: Balance real-time needs with API rate limits
  3. Selective Sync: Only sync necessary objects and fields
  4. Monitoring: Set up alerts for sync failures and performance issues

Data Quality

  1. Source Validation: Ensure clean data at the source level
  2. Mapping Validation: Test field mappings with sample data
  3. Duplicate Handling: Configure appropriate deduplication strategies
  4. Error Monitoring: Regularly review sync errors and data quality issues

Next Steps

Add Your First Destination

Follow our step-by-step guide to configure your first data destination.

Get Started →

📥 Browse Sources

See where you can get your data from to feed into destinations.

View Sources →

Need a destination that's not listed? Contact us to discuss custom integrations.