Grafana Tempo vs Jaeger vs Zipkin — Distributed Tracing Comparison (2026)

Distributed tracing shows you what happens inside a request as it flows through multiple services. In 2026, three open-source options dominate: Grafana Tempo, Jaeger, and Zipkin. They all store traces — but they're architected very differently.

Quick Comparison

Grafana Tempo

Tempo is the newest of the three, built specifically as a cost-efficient trace backend that stores traces in object storage (S3, GCS, Azure Blob).

Architecture

Applications → Tempo Distributor → Tempo Ingester → Object Storage (S3)
                                                          ↓
                               Grafana (TraceQL) → Tempo Querier

Tempo doesn't use Elasticsearch or Cassandra — it writes traces directly to S3 as Parquet/OTel files.

Key Strengths

Cost efficiency At 10M traces/day, S3 storage costs ~$5–15/month. Equivalent Elasticsearch storage costs $100–500+/month.

TraceQL Tempo's query language lets you search across all traces:

# Find all traces where checkout service took > 2 seconds
{ .service.name = "checkout" && duration > 2s }

# Find traces with errors on specific endpoint
{ .http.method = "POST" && .http.url =~ ".*checkout.*" && status = error }

# Find traces where payment service called db > 10 times
{ .service.name = "payment" } | count_over_time(1m) > 10

Grafana native integration Tempo was built by Grafana Labs. Integration with Grafana is first-class:

• Traces in Grafana Explorer
• Trace-to-logs correlation (click a trace → see Loki logs for that trace)
• Trace-to-metrics correlation (click a trace → see related Prometheus metrics)
• Alerts based on trace data

Low operational overhead Minimal configuration. No Cassandra cluster, no Elasticsearch cluster to maintain.

Weaknesses

• No standalone UI — requires Grafana
• Search requires tempodb index (adds some storage overhead)
• Less mature than Jaeger for very complex deployments

Jaeger

Jaeger was built by Uber and donated to the CNCF. It's the most mature option and battle-tested at massive scale.

Architecture

Applications → Jaeger Agent → Jaeger Collector → Storage (Cassandra/ES)
                                                        ↓
                                              Jaeger Query → Jaeger UI

Key Strengths

Maturity and stability Jaeger has been running in production at Uber, Netflix, and others for years. Its edge-case behavior is well understood.

Built-in UI Jaeger has its own web UI — no Grafana required. Good for teams that don't want to set up Grafana.

Flexible storage Supports Cassandra (designed for scale), Elasticsearch, and a local in-memory Badger store for testing.

Service dependency graph Jaeger generates a real-time service dependency graph — which services call which, with error rates and latency overlays.

Weaknesses

• Cassandra/Elasticsearch are expensive to operate
• Storage costs scale poorly — 1TB of traces in ES is expensive
• Less powerful query language than Tempo's TraceQL
• Alert integration requires external tooling

Zipkin

Zipkin is the oldest of the three — it originated at Twitter. It's simpler but less feature-rich.

Architecture

Applications → Zipkin Collector → Storage (MySQL/ES/Cassandra)
                                         ↓
                              Zipkin UI → Zipkin API

Key Strengths

Simplicity Zipkin is the easiest to set up. A single Docker container runs the entire stack (with in-memory storage).

docker run -d -p 9411:9411 openzipkin/zipkin

Broad language support Extensive libraries for Java, Python, Ruby, Node.js, Go — many frameworks auto-instrument for Zipkin.

Established format The Zipkin format (B3 headers) is widely supported. Many tools emit Zipkin-format traces natively.

Weaknesses

• Least powerful query capabilities
• No built-in alerting
• Falling behind Jaeger and Tempo in feature development
• Limited Grafana integration compared to Tempo

Deployment Comparison

Tempo on Kubernetes (simplest)

# values.yaml for Grafana Tempo
tempo:
  storage:
    trace:
      backend: s3
      s3:
        bucket: my-traces-bucket
        region: us-east-1
  retention: 336h  # 14 days

helm repo add grafana https://grafana.github.io/helm-charts
helm install tempo grafana/tempo-distributed \
  -n monitoring \
  -f values.yaml

Jaeger on Kubernetes

# Jaeger Operator install
kubectl create namespace observability
kubectl apply -f https://github.com/jaegertracing/jaeger-operator/releases/latest/download/jaeger-operator.yaml -n observability
 
# Jaeger instance with Elasticsearch
apiVersion: jaegertracing.io/v1
kind: Jaeger
metadata:
  name: jaeger
spec:
  strategy: production
  storage:
    type: elasticsearch
    elasticsearch:
      serverUrls: https://my-es-cluster:9200

Which to Choose

Choose Grafana Tempo if:

• You already use Grafana for dashboards/alerts
• Cost at scale matters (S3 is 10x cheaper than ES)
• You want trace-to-logs and trace-to-metrics correlation
• You're starting fresh in 2026

Choose Jaeger if:

• You need a built-in UI without Grafana
• You're running Cassandra already
• You want the most battle-tested option
• Your team knows Jaeger well

Choose Zipkin if:

• You need the simplest possible setup for development
• Your existing app stack already emits B3/Zipkin format traces
• You don't need alerting or advanced queries

For new Kubernetes-native setups in 2026: Grafana Tempo is the default recommendation. The S3-native storage model, TraceQL, and Grafana integration make it the most modern and cost-efficient choice.

Sending Traces to Any Backend

All three support OpenTelemetry Protocol (OTLP). Instrument once, switch backends:

# OpenTelemetry Collector config
exporters:
  otlp/tempo:
    endpoint: tempo-distributor:4317
    tls:
      insecure: true
  # Or switch to Jaeger:
  jaeger:
    endpoint: jaeger-collector:14250
    tls:
      insecure: true
 
service:
  pipelines:
    traces:
      receivers: [otlp]
      processors: [batch]
      exporters: [otlp/tempo]

Related: OpenTelemetry Complete Guide | Prometheus vs Datadog vs New Relic | Grafana Loki Log Aggregation Guide

Affiliate note: Grafana Cloud includes hosted Tempo, Loki, and Prometheus with a generous free tier (50GB traces/month free). Best way to try all three integrations without running infrastructure.