Streaming Data Platforms: Kafka, Pulsar, and Beyond

Streaming data platforms help teams publish and consume a steady flow of events. The two most popular open-source options are Apache Kafka and Apache Pulsar. Both store streams and support real-time processing, but they approach the problem with different design goals. Kafka focuses on a durable log with broad ecosystem support, while Pulsar separates storage and compute, offering strong multi-tenant capabilities and built-in geo-replication.

When you compare these systems, think about your priorities. Here are quick takeaways:

  • Kafka shines with a large ecosystem, mature tooling, and simple durability via topic partitions. It works well when teams already rely on Java/Scala clients and many connectors.
  • Pulsar stands out for multi-tenancy, scalable storage, and easy replication across regions. It can be a better fit for teams needing 24/7 isolation between projects or tenants.

Beyond these two, several options suit different needs. Cloud-native services like AWS Kinesis, Google Pub/Sub, or Azure Event Hubs offer managed simplicity but tie you to a cloud. Open-source alternatives such as Redpanda or NATS JetStream provide other trade-offs between performance, API compatibility, and operational effort. Some teams also explore RocketMQ for its strong ordering guarantees in certain workloads.

To decide, rate what matters most: latency, throughput, total cost, and the ease of operating the system. Look at the ecosystem: available connectors, schema tools, and monitoring. Assess your team’s skills and whether you need multi-tenant separation or simple, single-tenant setup. Finally, plan a small pilot—run a real use case, compare end-to-end latency, and measure maintenance tasks like upgrades and scaling.

Practical steps to start:

  • define a concrete streaming use case (e.g., clickstream to dashboards)
  • run a two-platform pilot with common tooling and a shared data model
  • enable security basics (TLS, authentication, authorization)
  • set up observability (metrics, dashboards, basic schema management)

Choosing the right platform is about balancing current needs with future growth. A thoughtful pilot can reveal the path that best fits your team and your data.

Key Takeaways

  • Kafka and Pulsar are strong, mature options with different architectural strengths.
  • Consider multi-tenancy, global replication, and operational complexity when choosing.
  • Start small with a clear use case, then scale focus on security, observability, and governance.