Available patterns
| Pattern | Description |
|---|---|
| Data caching | Cache fetch responses at the proxy layer to reduce broker load and repeated consumer reads |
| Large messages | Split oversized messages at produce time and reassemble them transparently at consume time |
| Large batches | Break produce requests that exceed broker limits into smaller batches automatically |
| CEL topic filtering | Define logical topics that filter records server-side using Common Expression Language expressions |
| SQL topics | Query Kafka topics using SQL semantics — filter, project and transform records at the proxy |
| Topic concentration | Map multiple virtual topics onto a single physical Kafka topic to reduce partition count and broker overhead |
When to use advanced patterns
- Reduce broker load — use caching to serve repeated fetch requests without hitting the broker every time
- Work around Kafka limits — large message and batch handling let you produce and consume data that exceeds
message.max.byteswithout reconfiguring brokers - Control data exposure — CEL and SQL topic filters let you expose a subset of a topic’s records to specific consumers without duplicating the underlying data
- Optimize partition usage — topic concentration consolidates logical namespaces onto fewer physical partitions, reducing overhead in multi-tenant environments