how sixty compares — OpenTelemetry-native observability and AI SRE
Sixty vs Dash0
A complete OTEL-native home for traces, metrics, logs and infrastructure, with Agent0 investigating and fixing incidents. Sixty is the narrower release detector.
What Dash0 is good at
Dash0 is what OpenTelemetry looks like when somebody turns the whole standard into a coherent product. Traces, metrics, logs, resources, service maps, infrastructure, Kubernetes, browser monitoring, synthetics, dashboards and alerts live together without a proprietary collection agent becoming the centre of the architecture.
Agent0 also makes this a materially different comparison from Grafana. It continuously investigates production, correlates signals, traces problems back to commits and can draft a pull request. If the goal is one OTEL-native system for both people and autonomous operations, Dash0 is the stronger and broader answer.
Its pricing is unusually legible for a full observability platform: each million metric points is $0.20 and each million spans, logs or web events is $0.60, with published retention and explicit Agent0 credits. Budgets, forecasts and ingestion filters make that usage model controllable rather than mysterious.
Dash0 costs $0.20 per million metric data points; $0.60 per million spans, logs or web events; Agent0 usage extra, as published on their pricing page in August 2026. Sixty is €14.99 a month, flat.
What Sixty does differently
Breadth is also the difference. Dash0 retains and lets you explore the telemetry, so cost follows the number of signals and somebody still decides what deserves a dashboard, check, automation or investigation. Sixty deliberately does not become the home for all of that data: it reduces useful traces and metrics into bounded release comparisons.
Sixty asks one narrower question automatically: what did this release change for each operation? It learns the before state, compares the next release, and hands the bounded evidence to the coding agent already in the editor. There is no per-signal bill, alert catalogue or AI-action meter.
They can run together. Keep Dash0 as the OTEL backend for exploration, logs, infrastructure and operations; add the Sixty OTLP/HTTP exporter beside it when release regression detection is the missing answer.
Side by side
The same 12 questions the full comparison asks of every tool, with the two rows Sixty loses left in.
| What is being compared | Sixty | Dash0 |
|---|---|---|
| What you set upBefore it can tell you anything at all. | Nothing. One command, no dashboards, no thresholds | Send OTEL data, then choose dashboards, checks, alerts and automations |
| Time to the first findingInstall to a sentence that names a cause. | Your next deploy | Live insights immediately; useful automation depends on the checks and context you configure |
| Compares one release to the lastAutomatically, without being asked a question. | Yes — every finding is one release against the one before | Release and commit context, but not Sixty’s automatic operation-by-operation baseline |
| Rows per call, queries per renderThe shape of what your database work returns, not how long it took. | Yes, this is the core signal | What your spans and semantic attributes contain |
| Page vitals per routeLargest paint, interaction response, layout shift. | Yes, broken down by country | Yes — website monitoring and web events |
| Failures that report successEmpty results, refused requests, buttons wired to nothing. | Yes — this is most of what it finds | Agent0 can investigate degradation; coverage follows the telemetry and checks you send |
| Names the change that caused itThe pull request in that deploy, not just the deploy. | Yes — the pull request in that deploy that touched the file the finding runs in | Yes — Agent0 can trace incidents to commits and draft pull requests |
| What your coding agent is handedThey all have an MCP server now. This row is what comes through it. | The before and after of the shape, the release that changed it, and the stack frames — unprompted, over MCP | Agent0 root-cause analysis and generated fixes or pull requests, charged by action |
| Data collected about your usersWhat ends up on somebody else’s server because you installed it. | None. No IDs, no cookies, no URLs. Session replay is off by default; switched on, every word is masked in the browser before it is sent | Whatever attributes, logs, traces and web events you choose to send |
| Infrastructure, logs, containersHosts, pods, queues — the layer under the application. | No | Yes — infrastructure and Kubernetes are first-class |
| Runtimes it measuresServer-side. Browser coverage is separate and mostly universal. | Node, Python, Go, Ruby and PHP, on Postgres, MySQL or MongoDB. Existing OpenTelemetry collectors add traces and metrics from any OTEL runtime; native agents remain higher fidelity. Any front end, any backend language | Everything instrumented through OpenTelemetry |
| Where the bill startsList price for a comparable product, read August 2026. | €14.99 a month, flat | Usage per telemetry signal, plus Agent0 credits and AI Coding Insights seats |
Which one to pick
Pick Dash0 when
- You want one OpenTelemetry-native platform for traces, metrics, logs, infrastructure and browser monitoring.
- You need dashboards, alerting, Kubernetes visibility, synthetics or long-term telemetry exploration.
- You want an autonomous SRE to investigate incidents and draft fixes across all of those signals.
- Consumption pricing fits your telemetry volume and you want budgets and filters to control it.
Pick Sixty when
- You already have an observability backend and only need release-aware problem detection.
- You want a flat application price rather than charges per telemetry signal and AI action.
- You want bounded evidence sent to your existing coding agent, not another telemetry workspace.
- You do not need logs, infrastructure, dashboards, alerts or a trace explorer.
These are not mutually exclusive and the honest answer is often both. Nothing here refuses to run alongside Dash0, and a lot of people keep it.
Questions people actually ask
Can Dash0 and Sixty use the same OpenTelemetry Collector?
Yes. Keep the Dash0 exporter in both pipelines and add otlphttp/sixty beside it. The collector fans out the same traces and useful metrics; Sixty does not require Dash0 to be removed or made secondary.
Is Agent0 the same as the Sixty MCP workflow?
No. Agent0 is an autonomous production SRE that investigates across Dash0 telemetry and consumes credits when it acts. Sixty detects release regressions, exposes bounded evidence over MCP, and lets the coding agent already working in your repository decide and implement the fix.
Which one should an OpenTelemetry team choose?
Choose Dash0 when you need the complete observability destination and operating workflow. Choose Sixty when you are keeping an existing destination and want a focused release detector. Using both is a normal collector fan-out configuration.
The other comparisons
Sixty vs Sentry
Best-in-class for the crash you can see. The gap is the failure that never throws — and what it stores about the person who hit it.
Product analytics, with error trackingSixty vs PostHog
Probably already in your app, and probably costing you nothing. It watches the funnel and the crash — not the query underneath either of them.
Platform-native monitoringSixty vs Vercel
Real page timings with one checkbox, and an agent that investigates your logs when something spikes. It stops where your database starts.
Full-stack observability platformSixty vs Datadog
Everything, for everyone, billed per host. Unbeatable if you run infrastructure; a lot of product to carry if you run one app on Vercel.
Full-stack observability platformSixty vs New Relic
The same breadth as Datadog on a friendlier meter, with a genuinely large free tier — and the same afternoon of setup before it says anything.
Open-source stack, hostedSixty vs Grafana Cloud
The most flexible and the most work. Prometheus, Loki, Tempo and OpenTelemetry, hosted for you — and still a project rather than a product.