Organizations syncing Salesforce data to PostgreSQL databases face a critical challenge: API limits that can halt integrations mid-operation, disrupting business processes and decision-making. When daily quotas exhaust, teams lose access to the real-time data visibility they need to serve customers effectively. Organizations with Enterprise Edition receive 1,000 API calls daily plus 1,000 per user license, making frequent synchronization impossible for large datasets. Change Data Capture, Bulk API 2.0, and database-centric platforms like Stacksync enable continuous synchronization without consuming REST API quotas.

Understanding Salesforce API Limit Constraints

Salesforce enforces strict daily API call limits that impact integration architecture decisions.

API Quota Breakdown by Edition

Salesforce allocates API calls based on your edition tier, creating significant constraints for growing organizations: While Salesforce offers a Developer Edition with 15,000 daily calls, mid-market and enterprise organizations typically operate on Enterprise, Unlimited, or Performance editions, where API limits become a critical constraint due to the 1,000 base + 1,000 per user formula.

• Enterprise Edition: 1,000 base calls plus 1,000 per user license

• Unlimited Edition: 1,000 base calls plus 1,000 per user license

• Performance Edition: 1,000 base calls plus 1,000 per user license

Understanding how different operations consume your API quota is essential for planning your integration strategy:

• Single record query: 1 API call

• Batch query (2,000 records): 1 API call

• Composite API request: 1 API call per subrequest

• Bulk API query: Does not consume REST API quota

Why Traditional Sync Methods Fail

Organizations attempting hourly Salesforce to PostgreSQL synchronization encounter three critical challenges that can derail their integration strategy:

1. Polling frequency constraints - Querying 50 objects hourly consumes 1,200 daily API calls (50 objects × 24 hours)

2. Record volume scaling - Large datasets require multiple paginated queries, each consuming quota

3. Concurrent integration conflicts - Multiple systems sharing the same API pool create resource competition

Method 1: Salesforce Change Data Capture

Change Data Capture (CDC) enables organizations to maintain synchronized data across systems without exhausting their API quotas, providing near-real-time event streams that capture every record change as it happens.

CDC Implementation Steps

Enable Change Data Capture in Salesforce

• In Salesforce Setup, navigate to Integrations, then select Change Data Capture

• Select standard objects (Account, Contact, Opportunity, etc.)

• Enable custom objects requiring synchronization

• Salesforce generates change events automatically

Configure Event Subscription

• Use CometD protocol to subscribe to change event channels

• Implement long-polling connection for event delivery

• Process ChangeEventHeader containing operation type, entity ID, and changed fields

• Handle event replay using ReplayId for guaranteed delivery

PostgreSQL Data Pipeline

• Parse incoming change events in JSON format

• Map Salesforce field names to PostgreSQL column names

• Execute INSERT, UPDATE, or DELETE operations based on event type

• Maintain replication lag monitoring to ensure synchronization freshness

CDC Advantages and Limitations

Benefits

• Zero REST API quota consumption

• Sub-second change notification latency

• Selective field change tracking reduces processing overhead

• Automatic retry through replay mechanism

Challenges

• Organizations need Salesforce Enterprise Edition or higher to access CDC functionality

• CDC retains events for only 24 hours, meaning any system downtime longer than a day could result in missed data changes and synchronization gaps

• Custom CDC implementation demands 2-3 months of initial development plus ongoing maintenance—exactly the kind of infrastructure burden Stacksync eliminates, allowing your team to focus on business innovation instead of integration plumbing

• Long-polling connections need robust error handling

Method 2: Bulk API 2.0 Optimization

Bulk API 2.0 processes large data volumes through asynchronous jobs that operate outside REST API limits.

Bulk API Best Practices

Job Configuration Strategy

Create optimized bulk query jobs:

Configure your bulk query job with these essential parameters:

• Operation: query

• Object: Account

• Content type: CSV

• Column delimiter: COMMA

• Line ending: LF

SOQL Query Optimization

Design queries to minimize result size: - Select only required fields instead of wildcards - Apply filter criteria to reduce record counts - Use indexed fields in WHERE clauses for performance - Avoid SOQL queries with cross-object relationships when possible

Batch Processing Schedule

Implement daily synchronization windows: 1. Submit bulk query job during off-peak hours (midnight - 4 AM) 2. Poll job status every 30 seconds until completion 3. Download result CSV files in parallel 4. Parse CSV and bulk insert to PostgreSQL using COPY command 5. Update synchronization metadata with last run timestamp

Bulk API Performance Metrics

Expected Throughput

• 10 million records: 30-45 minutes processing time

• CSV download bandwidth: 50-100 MB/s depending on region

• PostgreSQL COPY insertion: 100,000-500,000 rows/second

Resource Consumption

• Bulk API quota: 15,000 batches per rolling 24 hours

• File storage: Temporary CSV files require local disk space

• Memory overhead: Stream processing recommended for large files

Method 3: Database-Centric Sync with Stacksync

Stacksync eliminates API limit concerns through native database synchronization architecture.

How Stacksync Bypasses API Constraints

Core architectural differences:

1. Direct database replication - Stacksync maintains bidirectional sync channels that replicate changes without API intermediaries

2. Consolidated API usage - Single connection per Salesforce org regardless of integration count

3. Intelligent change detection - Monitors Salesforce modification timestamps to pull only updated records

4. Built-in rate limiting - Stacksync automatically manages API consumption across all your integrations, preventing quota exhaustion and ensuring uninterrupted data flow for business-critical operations

Implementation Timeline

Day 1: Quick Initial Setup and Configuration

• Connect Salesforce org with OAuth authentication

• Configure PostgreSQL database connection

• Map Salesforce objects to database tables

• Select synchronization direction (one-way or bidirectional)

Day 2-3: Historical Data Migration

• Stacksync performs initial bulk transfer using optimized API patterns

• Progress monitoring through built-in dashboard

• Automatic retry handling for transient failures

• No interruption to existing Salesforce operations

Day 4+: Continuous Synchronization

• Real-time change detection activated

• Stacksync delivers sub-minute synchronization latency, ensuring your teams always work with current data

• Comprehensive audit logging for compliance

• Built-in data validation and transformation

How ACERTUS Eliminated API Limit Concerns

The logistics leader was hitting Salesforce API limits daily while syncing shipment data to PostgreSQL. After implementing Stacksync, ACERTUS achieved:

• 100% elimination of API quota issues across 15+ integrations

• 80% reduction in engineering time spent on integration maintenance

• Sub-60-second data synchronization for real-time shipment visibility

'Stacksync removed the constant worry about API limits and freed our team to focus on building features that differentiate our business,' said VP of Technology, Alex Marinov.

Hybrid Approach for Optimal Results

Many organizations achieve optimal results by combining multiple synchronization methods, matching each approach to specific business requirements and data types.

Recommended Architecture

Real-Time Critical Data (CDC or Stacksync)

• Opportunity stage changes

• Case status updates

• Contact information modifications

• Account ownership transfers

Batch Analytics Data (Bulk API)

• Historical trend analysis datasets

• Data warehouse full refreshes

• Compliance audit exports

• Archived record transfers

Configuration Objects (Manual/Scheduled)

• Picklist value definitions

• Custom field metadata

• Workflow rules documentation

• User permission sets

Monitoring and Alerting

Implement monitoring across synchronization methods:

Key Metrics to Track

• API quota utilization percentage (alert at 80% threshold)

• Synchronization lag time (alert if exceeds 5 minutes for critical objects)

• Failed record count (alert on any failures for financial data)

• Data consistency validation results (daily checksum comparisons)

Alert Escalation Workflow

1. Warning notification at 80% API quota consumption

2. Critical alert at 95% with automatic rate limiting

3. Emergency failover to Bulk API if quota exhausted

4. Executive notification if synchronization lag exceeds SLA

Getting Started Recommendations

Stacksync Is the Right Choice When:

• API limit management creates operational burden

• Multiple integrations share Salesforce API quota

• Sub-minute synchronization latency required

• Your lean engineering team (typically 5-15 specialists) needs to focus on core product innovation rather than building and maintaining integration infrastructure

• Compliance audit trails needed

Choose Custom CDC If

• Real-time requirements mandate sub-second latency

• Engineering team available for long-term maintenance

• Selective object synchronization reduces scope

• Existing event-driven architecture in place

Choose Bulk API If

• Daily batch synchronization meets business requirements

• Large historical datasets need periodic refresh

• Engineering resources available for job orchestration

• Your use case involves periodic analytics refreshes rather than operational processes requiring real-time data access

Ready to eliminate API limit concerns and achieve reliable, real-time Salesforce synchronization? Start your free 14-day Stacksync trial today, no credit card required. Our team will help you configure your first sync and demonstrate how quickly you can move from setup to production, typically within days rather than months of custom development.