Jaeger vs Zipkin

Overview

Jaeger and Zipkin are both open-source distributed tracing systems that help engineers follow requests across microservices and diagnose latency. Zipkin, originating at Twitter, is the older and lighter of the two. Jaeger, created at Uber and now a graduated CNCF project, is designed for cloud-native, large-scale deployments and is closely aligned with the OpenTelemetry ecosystem.

Key Differences

Both share core tracing concepts—spans, traces, and context propagation—and both support multiple storage backends such as Cassandra and Elasticsearch, so on fundamentals they are similar. The differences are in scale orientation, momentum, and polish.

Jaeger is built with a cloud-native architecture and scalable components, and it has strong ecosystem momentum, including first-class OpenTelemetry support and a place in the CNCF landscape. Its UI is richer, offering features like service dependency graphs and more detailed trace analysis. This makes Jaeger a natural fit for large Kubernetes-based systems and teams standardizing on CNCF tooling.

Zipkin's strength is simplicity. It is lightweight and exceptionally easy to start—you can run it as a single process and begin tracing quickly—which suits smaller systems, quick experiments, or environments that value minimal operational overhead. It is mature and widely compatible, including with OpenTelemetry, though its development moves more slowly and its UI is more basic.

When to Choose Jaeger

Choose Jaeger for cloud-native, large-scale tracing where you want scalable architecture, a richer UI with dependency analysis, and tight alignment with CNCF and OpenTelemetry. It is the forward-looking default for modern microservice platforms.

When to Choose Zipkin

Choose Zipkin when you want lightweight, quick-to-deploy tracing for smaller or simpler systems, or when existing services are already instrumented for it. Its low operational footprint is a genuine advantage when you do not need Jaeger's scale.

Verdict

Both are capable, and OpenTelemetry increasingly decouples instrumentation from either backend, letting you switch with less friction. Jaeger has the momentum, scalability, and richer features that make it the common choice for new cloud-native deployments. Zipkin remains a solid, simple option for smaller setups and legacy compatibility. For most new projects, Jaeger (fed by OpenTelemetry) is the safer long-term bet.