The Claim Check Pattern (Processing large payloads efficiently)
The Claim Check Pattern is an enterprise integration pattern that allows a system to send lightweight messages by replacing large or sensitive payloads with a reference (a “claim check”). The actual payload is stored in a shared, reliable datastore. Consumers of the message can use the claim check to retrieve the payload when needed.
In other words, instead of passing a heavy box around, you pass around a receipt (the claim check) that lets you pick up the box from storage later.
How It Works
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Producer stores payload - The producer saves the large data payload in a shared storage system.
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Producer sends claim check - Instead of embedding the payload in the message, the producer sends a lightweight message containing only metadata and a reference.
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Consumer receives claim check - The consumer processes the message and uses the claim check to fetch the actual payload from the shared storage.
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Consumer processes payload - Once retrieved, the consumer can process the payload just like it would in a traditional message-driven system.
Benefits
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Reduced network overhead: Messages are small and fast to transmit.
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Improved scalability: Services handle less data in transit, reducing strain on message brokers.
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Flexible payload storage: Payloads can be stored in scalable, durable stores (e.g., Amazon S3, Redis, or a blob store).
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Security and access control: Sensitive data doesn’t travel with every message—access can be controlled at the storage layer.
When to Use the Claim Check Pattern
The Claim Check Pattern is especially useful when:
- Payloads are too large to efficiently pass through a message bus.
- Message throughput needs to be optimized.
- Data security requires separating metadata from sensitive content.
If payloads are small, frequent, and critical to message context, a direct messaging approach may be simpler and more efficient.
Conclusion
The Claim Check Pattern is a powerful tool to know when designing systems. By separating heavy payloads from lightweight messages, it helps distributed systems achieve scalability, performance, and some level security. Like any pattern, it comes with trade-offs, but when applied in the right context it can greatly improve system efficiency and reliability.