How to Prevent Duplicate Records in an API Integration

When one system sends data to another, a timeout does not always mean the receiver failed to process the request. The sender may retry while the original operation is still completing, creating duplicate customers, invoices, or tickets. Integrations should be designed for repeated delivery rather than assuming every message arrives exactly once.

Use a stable identity for each operation

Assign an idempotency key or event identifier that remains the same across retries. The receiver can store the key and return the original result instead of repeating the business action. Choose keys that identify the operation, not only a mutable record that may later change.

Make retry behavior explicit

• Retry transient network failures with bounded backoff and jitter.
• Do not retry permanent validation or authorization errors without correcting the cause.
• Track messages that exceed retry limits in a queue for investigation.
• Record correlation IDs and timestamps across both systems.
• Build a reconciliation report to compare source and destination records.

Test failure cases

Simulate a response timeout after the receiver commits the change, then verify that a retry does not duplicate the result. Also test out-of-order delivery, partial failures, and replay after recovery.

Informatix Systems lists custom software and API integration related services. A design review can map event ownership, retry behavior, and reconciliation for a specific workflow. Contact Informatix Systems to discuss duplicate records between systems.