Kafka vs. Pulsar: Choosing Your Streaming Platform
| Aspect | Apache Kafka | Apache Pulsar |
|---|---|---|
| Storage Model | Brokers own local segment logs. KRaft (or ZooKeeper) manages metadata. | Brokers handle serving; Apache BookKeeper stores data segments; ZooKeeper coordinates. |
| Scaling | Add brokers/partitions; rebalancing can be heavy. | Compute and storage scale independently; segments moved automatically. |
| Multi-Tenancy | Namespaces via ACLs, but often cluster-per-tenant. | Tenants & namespaces built-in; quota and isolation per tenant. |
| Messaging Model | Pub/sub, at-least-once, transactional exactly-once, log compaction. | Pub/sub plus queue semantics (exclusive/shared/failover subscriptions). |
| Geo-Replication | MirrorMaker 2, Confluent Cluster Linking. | Built-in async replication with per-namespace policies. |
When Kafka Excels
- Mature ecosystem (Kafka Connect, Streams, ksqlDB, Confluent Cloud).
- Massive ecosystem of managed services and community tooling.
- Simple operational model for teams already invested in Kafka.
- High-throughput append-only workloads with predictable retention.
When Pulsar Shines
- Multi-tenant clusters serving many teams simultaneously.
- Use cases requiring both queue and streaming semantics in one platform.
- Infinite retention with tiered storage and low-cost cold data.
- Rapid horizontal scaling without moving partitions manually.
Operational Considerations
- Deployment: Kafka 3.x supports KRaft (no ZooKeeper). Pulsar still depends on ZooKeeper + BookKeeper, so plan for three-stateful tiers.
- Tooling: Pulsar IO connectors exist but are less extensive than Kafka Connect’s catalog. Evaluate coverage before committing.
- Latency: Both deliver sub-10 ms p99 on tuned hardware; benchmark with your workloads.
- Cost: Pulsar’s separation of compute/storage enables disaggregated scaling; Kafka typically ties CPU and disk together.
Migration Thoughts
- Moving from Kafka → Pulsar: use connectors (StreamNative Offloader, DataStax Astra Streaming) or mirror topics via NiFi/Flink.
- Pulsar → Kafka: rely on Pulsar IO Kafka sink/source or custom consumers.
- In either direction, align schema governance (Confluent Schema Registry vs Pulsar schemas) and consumer offsets.
Summary
Pick the technology that aligns with your operational model and roadmap. Kafka remains the default for many organisations due to ecosystem maturity. Pulsar is compelling when multi-tenancy, storage disaggregation, or built-in queue semantics are decisive.