Integration / Apache Pulsar Interview questions
What is the difference between Pulsar and Kafka's storage architecture?
Kafka couples compute and storage on the same broker process - each broker both serves client traffic and stores partition data on its own local disk, so scaling storage means scaling brokers too, and a broker failure requires replica reassignment and data catch-up.
Pulsar splits these roles: brokers are stateless and only serve traffic, while BookKeeper bookies durably store the actual data as replicated ledgers - this segmented architecture lets broker count (compute) and bookie count (storage) scale independently based on which resource is actually the bottleneck.
The practical payoff is that Pulsar broker failover is fast (just reassign topic ownership, no data to catch up), while Kafka's tighter coupling can make rebalancing and scaling operations more disruptive at large scale.
| Kafka | Pulsar |
| Compute and storage coupled on the broker | Compute (broker) and storage (bookie) separated |
| Broker failure needs replica catch-up | Broker failover reassigns ownership only, no data movement |
| Storage scales together with broker count | Storage (bookies) scales independently of brokers |
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