Jaeger vs Zipkin
On the evidence we track, Jaeger leads this comparison with a composite score of 59/100. Scores are only directly comparable because these tools share a category; the full breakdown and every source is below.
Capabilities
Feature-by-feature on the axes that matter for distributed tracing tools. “-” means undocumented, not absent.
What each one is
The product in its own terms, so the numbers below have context.
Jaeger
LeaderA backend that collects execution traces from microservice-based applications and provides analysis tools to understand system behavior and diagnose issues. Teams use it to track how requests move through their services and identify where delays or errors occur.
Zipkin
Collects timing and dependency data from instrumented applications to troubleshoot latency issues. Provides a web interface for querying traces by service, operation, tags, or duration, and displays how requests flow through the service architecture.
Pricing
List pricing as published by each vendor, with the date we read it. Always verify at the source before you buy.
Platform & deployment
Where each product runs and how it can be hosted. A dash means undocumented, not unsupported.
Integrations
What each product connects to. Counts come from the vendor's own integration directory where one exists.
- Elasticsearch
- OpenSearch
- Kafka
Jaeger
Leader- Cassandra
- ClickHouse
- Badger
- Memory
Zipkin
- HTTP
- Apache ActiveMQ
- gRPC
- RabbitMQ
- Apache Pulsar
- Apache Cassandra
- Brave
Comparison generated from independently-sourced facts. Every value links to its source and retrieval date. See the method.