This article compares and contrasts the applications, reviewing their similarities and differences, ease of use, security, and use cases.
Messaging technologies like Apache Kafka and Apache Pulsar provide core middleware "plumbing" for modern applications. They enable real-time data streams between systems and support event-driven architectures. Both open-source projects have seen wide adoption. But which one is right for your needs? Here's an in-depth look at Kafka vs. Pulsar and their key differences.
A Brief Background
Apache Kafka originated at LinkedIn in 2011 as a distributed messaging system to connect their internal systems. It was open-sourced and later became a top-level Apache project in 2012. Kafka provides publish-subscribe messaging, distributed commit logs, and stream processing.
Apache Pulsar was originally developed by Yahoo in 2013 to power core messaging across their systems. It was open-sourced by Apache in 2018. Pulsar offers similar publish-subscribe and queuing functionality as Kafka but also supports other patterns like multi-tenancy.
Both projects have broad users including major tech giants, banks, retailers, and more. While their core capabilities overlap, there are some key architectural differences to weigh for your use case.
As TIBCO CTO Rajeev Kozhikkattuthodi shared with me at TIBCO Next: "Kafka is brilliant for an entire slew of use cases, including analytics and including sort of capabilities that require data distribution, but not so much around to scale that out for transactional use cases."
Key Technical Differences
Multi-tenancy - Pulsar was built for multi-tenant environments and natively separates tenants. Kafka requires additional components like Kubernetes for multi-tenancy.
Persistence - Pulsar uses Apache Bookkeeper for "at least once" durable persistent messaging. Kafka uses its own commit log.
Routing - Pulsar uses a triple-replicated metadata store for routing. Kafka brokers handle routing directly.
Subscription types - Pulsar has exclusive, shared, and failover subscription modes. Kafka just supports consumer groups.
Deployment - Pulsar uses container-first deployment on Kubernetes. Kafka relies on physical/virtual machines.
Codebase - Pulsar was built on modern Java8+ code. Kafka code has legacy aspects.
Scaling - Kafka scales by adding brokers. Pulsar scales brokers and Bookkeeper storage separately.
Performance and Scalability
Both Kafka and Pulsar can scale to process high volumes of messages. However, benchmarks show Pulsar generally requires fewer infrastructure resources than Kafka to support equivalent throughput. Pulsar also provides lower end-to-end latency.
Pulsar's streamlined publish-subscribe messaging architecture avoids Kafka's queuing overheads. Its multi-layer design also allows Pulsar to scale specific components on demand. Kafka has a monolithic architecture that scales as one unit.
Ease of Operation
Managing Pulsar clusters, tenants, topics, subscriptions and more can mostly be handled through admin APIs and CLI. Kafka requires dealing with Zookeeper directly for cluster coordination.
With fewer moving parts than Kafka, Pulsar reduces some operational complexity. Critical cluster metadata is replicated for high availability, which removes Zookeeper as a dependency.
As Rajeev notes, "Operating Kafka is, is a completely different ballgame from operating either Pulsar or a more traditional sort of messaging technology."
Security
Pulsar supports authentication using OAuth 2.0, Athenz, TLS client certificates, and other mechanisms. Authorization uses ACLs to control access. Encryption ensures confidentiality.
However, Kafka provides more mature security after a decade of development. For instance, Kafka supports SASL authentication and network encryption via SSL. Recent versions have fine-grained ACLs.
For stringent security requirements, Kafka currently offers a wider range of advanced capabilities than Pulsar.
Use Cases
Messaging is a universal pattern across many domains. Both Kafka and Pulsar can support:
Real-time data pipelines
Microservices communication
Event-driven systems
Streaming analytics
Application integration
MQ replacement
For high-throughput use cases like metrics, logging, and operational data streams, Kafka remains a top choice. Its ability to act as a distributed commit log makes it ideal for these high-ingestion workloads.
For lower-latency messaging, Pulsar is very performant. Its multi-tenancy, subscription flexibility, and operability also make it well-suited to SaaS applications and multi-tenant use cases.
The Verdict
Apache Pulsar shows a lot of promise as a next-generation messaging system. It offers a cloud-native architecture and delivers lower latency and simpler management than Kafka in many cases.
Kafka benefits from a first-mover advantage, a larger ecosystem, proven security model and is battle-tested at a massive scale. Kafka remains the "safe choice" for most real-time messaging use cases right now.
For newer applications built on microservices, containers, and multi-tenancy, Pulsar has many advantages. Its design overcomes limitations of Kafka's legacy architecture.
The ideal option depends on your specific requirements and environment. Both messaging platforms are open source and deliver value. Review the key architectural differences and assess the pros and cons based on your use case.
Over time, Pulsar is well-positioned to potentially disrupt Kafka by delivering a messaging infrastructure designed for the modern world. But Kafka's maturity makes it hard to surpass - for now. The scale of adoption and supporting ecosystem take years to develop.
Keep tracking the progress of both projects. They may converge or continue distinguishing themselves through different strengths. For mission-critical messaging needs, you cannot go wrong today with either Apache Kafka or Apache Pulsar.