| Aspect |
Apache Pulsar |
Apache Kafka |
| Architecture |
Separates storage and serving layers using Apache BookKeeper for
storage and brokers for message routing.
|
Combines storage and serving layers, with brokers handling both
message routing and storage.
|
| Scalability |
Designed for horizontal scalability by adding brokers to increase
processing capacity.
|
Scalable, but requires careful configuration of brokers, ZooKeeper,
and RocksDB.
|
| Performance |
Better throughput and latency in some benchmarks, optimized for
high-performance tasks.
|
Performance can be improved through careful configuration and tuning.
|
| Message Delivery |
Supports all message delivery models: at-most-once, at-least-once, and
exactly-once out of the box.
|
Primarily supports at-least-once; additional configuration is needed
for exactly-once delivery.
|
| Multi-Tenancy |
Native support for multi-tenancy, with isolated namespaces and
resource allocation.
|
Limited support for multi-tenancy, requiring extra configuration and
management.
|
| Geo-Replication |
Built-in support for geo-replication across multiple regions.
|
Requires additional configuration for geo-replication.
|
| Security |
Comprehensive security with SSL/TLS, SASL, and Kerberos built-in.
|
Supports encryption and authentication but requires more manual
configuration.
|
| Ecosystem |
Growing ecosystem, but still behind Kafka in terms of breadth and
depth.
|
More mature ecosystem with a wide range of connectors, integrations,
and tools.
|
| Community |
Smaller but active and growing community.
|
Larger, well-established community with thousands of contributors.
|
Conclusion
Apache Pulsar and Kafka are powerful platforms that cater to different
use cases. Pulsar excels in multi-tenancy, geo-replication, and
high-performance streaming, while Kafka’s mature ecosystem and community
make it a popular choice for event-driven architectures and traditional
data processing. Choose based on your specific use case and ecosystem
requirements.