5 Salesforce Integration Patterns for Enterprise Systems

# 5 Salesforce Integration Patterns for Enterprise Systems Salesforce rarely lives in isolation. Most enterprises need to connect it with ERP systems, data warehouses, legacy applications, and modern SaaS tools. Here are the five integration patterns we use most frequently, with real-world examples. ## 1. Real-Time Bi-Directional Sync **Use Case**: Keeping Salesforce and SAP in sync for orders and customer data **Pattern**: Platform Events + REST API callouts - Salesforce publishes Platform Events when records change - Integration layer subscribes and transforms data - Updates pushed to external system via API - Webhooks from external system trigger Salesforce updates **Gotcha**: Handle failures gracefully. We use retry queues and dead letter handling for records that fail to sync. ## 2. Scheduled Batch Data Transfer **Use Case**: Nightly sync of product catalog from ERP to Salesforce **Pattern**: Scheduled Apex + Bulk API - Scheduled Apex job runs daily at 2 AM - Fetches changed records from external system - Uses Bulk API for efficient large-scale updates - Email notification on success/failure **Gotcha**: Governor limits matter. Batch size and API call optimization are critical. ## 3. Event-Driven Workflows **Use Case**: Trigger Salesforce workflow when invoice paid in accounting system **Pattern**: Outbound Messages or Platform Events - External system calls Salesforce REST API when event occurs - Triggers Process Builder or Flow - Can invoke Apex for complex logic - Audit trail maintained in Salesforce **Gotcha**: Authentication and security. Use Named Credentials and OAuth for secure connections. ## 4. Data Warehouse Reporting **Use Case**: Combine Salesforce data with other sources in Snowflake **Pattern**: Incremental ETL with change data capture - Salesforce Bulk API extracts changed records daily - Data loaded into staging tables - Transformed and merged with other enterprise data - Powers unified BI dashboards **Gotcha**: Field-level security and sharing rules don't apply to extracted data. Handle sensitive data appropriately. ## 5. Middleware Integration Hub **Use Case**: Salesforce as hub connecting to 10+ systems **Pattern**: MuleSoft or custom integration platform - Centralized integration layer handles all transformations - Reusable connectors and mappings - Error handling and monitoring in one place - Reduces point-to-point complexity **Gotcha**: Additional infrastructure costs. Only justified for complex integration landscapes. ## Choosing the Right Pattern Consider: - **Volume**: How many records per day? - **Latency**: Real-time or batch acceptable? - **Direction**: One-way or bi-directional? - **Complexity**: Simple field mapping or business logic? The right pattern depends on your specific needs. We've successfully deployed all five across different client scenarios.