Kafka
Map every Kafka topic to the producers that publish to it and the consumers that read from it across source systems, warehouses, and BI tools.
Streaming & CDCWhy Kafka matters
Kafka is the real-time backbone connecting source systems, microservices, warehouses, and operational tools. But lineage typically stops at its boundary: upstream producers do not know who consumes their events, and downstream consumers do not know what produced them. This makes Kafka the biggest blind spot in cross-system lineage.
Typedef connects Kafka topics to every producer and consumer across the full platform, so you can trace data through streaming infrastructure the same way you trace it through batch pipelines.
What Typedef unlocks
Bridge the streaming gap
Connect Kafka topics to producers and consumers across source systems, microservices, warehouses, and BI tools so lineage spans real-time and batch.
Cross-boundary impact analysis
Before modifying a topic schema or retiring a producer, see the full blast radius across both streaming and batch systems.
Root cause tracing through events
When a warehouse table has bad data, trace the issue back through Kafka to the original producer and event that caused it.
Topic and stream cleanup
Retire unused topics, consolidate redundant event streams, or migrate between streaming platforms with full visibility into every downstream dependency.
Related integrations
Bridge the gap between execution order and data dependencies so pipeline failures are scoped by business impact.
See the full downstream blast radius before a connector change ripples through everything that depends on it.
See the full picture: what feeds every table and what depends on it across the stack.
Trace dependencies across notebooks, Delta tables, Unity Catalog, and every tool outside Databricks that depends on them.