OpenTelemetry vs Prometheus: differences and fit

Short answer

Prometheus is a metrics-only system: a pull-based time-series database with a powerful query language (PromQL) and an alert manager. OpenTelemetry is a full instrumentation standard for traces, metrics, and logs, with a wire protocol (OTLP) and a Collector that routes telemetry to any backend.

They are not direct substitutes. Prometheus is great at scraping infrastructure metrics. OpenTelemetry is great at unified application telemetry. Most modern stacks use both — OpenTelemetry for traces and logs, Prometheus or OTel metrics for time-series — and many teams use the OpenTelemetry Collector to bridge between them.

What each project actually covers

Prometheus is a single product: a server that scrapes HTTP metrics endpoints, stores them locally, evaluates rules, and serves PromQL queries. It does not collect traces or logs. It scales by sharding (Thanos, Mimir, Cortex) and federates by being scraped itself.

OpenTelemetry is not a product — it is a specification, a set of language SDKs, and a Collector. It defines a wire format (OTLP) for traces, metrics, and logs. There is no built-in storage; you choose a backend (Telemtra, Jaeger, Tempo, Loki, Mimir, vendor SaaS) that accepts OTLP.

If your only need is "scrape /metrics from a few services and chart it," Prometheus is fast and battle-tested. If you also need traces and logs in the same place, you have outgrown Prometheus alone.

Data model differences

Prometheus has four metric types: counter, gauge, histogram, summary. OpenTelemetry has counters, up/down counters, gauges (observable), and histograms (explicit and exponential bucket), plus traces and logs. The OTel histogram with exponential buckets is more memory-efficient at high cardinality than the Prometheus equivalent.

Labels in Prometheus are key-value strings on a metric. OpenTelemetry's equivalent is "attributes," which apply to spans, log records, and metric data points. OTel also has the concept of a "resource" — attributes shared by everything an entity emits (service.name, deployment.environment, host.name) — which is what makes cross-signal correlation work.

Push vs scrape

Prometheus pulls: the server scrapes /metrics from each target on an interval. This works well in long-lived infrastructure but is awkward for serverless, batch jobs, and short-lived processes (you need a Pushgateway).

OpenTelemetry pushes: SDKs export OTLP to a Collector or backend on a schedule. This handles serverless and ephemeral workloads naturally. For workloads where pull is preferred, the OpenTelemetry Collector has a prometheus receiver that scrapes /metrics endpoints and converts them to OTLP, and a prometheusremotewrite exporter that pushes OTLP metrics into a Prometheus-compatible store.

Cardinality and labels

Both systems can blow up if you put unbounded values into labels (user IDs, request paths, trace IDs). The standard discipline is the same: keep label cardinality enumerable. OTel's resource attributes help by separating per-emission attributes (likely high-cardinality) from per-service attributes (low-cardinality), which makes it easier to control.

Using OpenTelemetry and Prometheus together

The most common production pattern: keep Prometheus for what it is good at (scraping kube-state-metrics, node_exporter, blackbox probes) and use OpenTelemetry for application traces, logs, and app-emitted metrics. Wire them together with the Collector:

receivers:
  prometheus:
    config:
      scrape_configs:
        - job_name: node-exporter
          static_configs:
            - targets: [node-exporter:9100]
  otlp:
    protocols:
      http:
        endpoint: 0.0.0.0:4318

exporters:
  otlphttp/telemtra:
    endpoint: https://ingest.telemtra.io
    headers:
      x-api-key: ${env:TELEMTRA_API_KEY}

service:
  pipelines:
    metrics:
      receivers: [prometheus, otlp]
      exporters: [otlphttp/telemtra]

That single Collector deployment scrapes Prometheus targets and ingests OTLP from apps, then forwards everything to Telemtra as OTLP.

Where Telemtra fits

Telemtra is an OTLP-native backend. It accepts metrics whether they originate from an OTel SDK or from Prometheus-scraped targets that the Collector converted. You get unified search across logs, traces, and metrics with consistent service and environment attributes — something Prometheus alone does not offer because it has no logs and no traces.

For teams currently running Prometheus alongside a separate log and trace stack, Telemtra collapses the three into one workspace without forcing you to abandon Prometheus exporters you already trust.

How to choose

Use Prometheus alone if you only need infrastructure metrics, your team already operates Prometheus well, and you do not need traces or correlated logs.
Use OpenTelemetry alone if you are starting fresh and want one SDK and one wire format for everything.
Use both if you already have Prometheus scrape configs you trust, but want to add traces and logs. Route both into the same Collector and forward to one OTLP backend.

See What is OTLP? for the protocol Telemtra accepts. See the Collector quickstart for a working pipeline. Start a free Telemtra workspace to test the combined setup.

OpenTelemetry vs Prometheus.