# Dynatrace vs Uptrace: A Complete Comparison for 2026
Put Dynatrace and Uptrace next to each other and you're really comparing two answers to a question most vendors never ask out loud: how much of your observability platform do you actually want to own? Dynatrace's answer is none of it. OneAgent, Smartscape, Grail, and Davis are proprietary top to bottom, hosted in Dynatrace's cloud, and you pay for the privilege of never touching the infrastructure underneath. **Uptrace's answer is all of it, if you want to.** It's OpenTelemetry-native by exclusive design, stores everything in ClickHouse, and ships a fully free, AGPL-licensed Community Edition you can run on your own infrastructure with no data limits and no feature gates.
That's not a small difference dressed up as a big one. Dynatrace is one of the deepest, broadest, most automated observability platforms that exists: OneAgent auto-instruments a host the moment it's installed, Davis has been producing deterministic, topology-aware root cause since 2017, and the platform reaches into SAP, VMware, and the mainframe in ways almost nothing else in the category does. **Uptrace doesn't compete on any of that, and isn't trying to.** It has no infrastructure monitoring beyond what OTel exporters report, no AI, no application security, no digital experience monitoring, and no seat model at all, because it has no concept of a seat. What it has is a lean, fast, OTLP-only backend on ClickHouse, a hard budget cap that actually stops billing rather than just alerting on it, and a price built around one dimension: how much data you send.
So this comparison resolves along a line most Dynatrace comparisons don't: **maturity and breadth against openness and cost control.** If your organization needs deterministic causal AI across a sprawling hybrid estate and can absorb a serious consumption bill for it, Dynatrace does things Uptrace was never built to do. If your applications are already instrumented with OpenTelemetry and you want a fast, self-hostable backend without per-user math or vendor lock-in, Uptrace does the job Dynatrace was never built to do cheaply. The rest of this comparison works through where each bet pays off, using current 2026 pricing and product status.
## Quick comparison at a glance
| Feature | Dynatrace | Uptrace |
|---|---|---|
| **Primary purpose** | Full-stack enterprise observability | OTLP-native APM backend on ClickHouse |
| **Gartner Observability MQ 2026** | Leader (16th consecutive time) | Not evaluated (different category) |
| **Deployment model** | SaaS (Grail) + Managed (self-hosted) | Cloud (EU), self-hosted (free), on-premises |
| **Free tier** | 15-day trial | Yes (cloud + unlimited free self-hosted) |
| **Pricing model** | Consumption rate card (DPS) | Data volume + datapoints, no seats |
| **Per-user fee** | No (but Full-Stack gates seat access indirectly via cost) | No |
| **Hard budget cap** | No | Yes |
| **Instrumentation** | OneAgent (auto-inject) or OTel | OTLP only (no proprietary agent) |
| **Distributed tracing** | Yes (method-level, PurePath) | Yes (OTel-native, ClickHouse JSON spans) |
| **Topology mapping** | Smartscape (automatic) | No |
| **Code-level profiling** | Yes (PurePath, thread-level) | No |
| **Infrastructure monitoring** | Deep (cloud, SAP, VMware, mainframe) | Kubernetes-first (via OTel exporters) |
| **Log management** | Mature (Grail, DQL) + query fees | Yes (ClickHouse, $0.10/GB or included) |
| **Digital experience / RUM** | Yes (per session) | No |
| **Root cause AI** | Davis (deterministic, topology-wide, GA since 2017) | No |
| **MCP server** | Yes (GA, remote + local) | No |
| **Application security** | Yes (runtime vuln + protection + posture) | No |
| **Self-hosted option** | Yes (Managed, licensed) | Yes (free, AGPL Community Edition) |
| **Open source** | No | Yes (Community Edition) |
| **Grafana compatibility** | Limited | Yes (Prometheus + Tempo datasource) |
| **Incident management** | Not included (integrate PagerDuty/ServiceNow) | Alerting only (email, Slack, webhook) |
| **Status pages** | No | No |
| **SOC 2 Type II** | Yes | In progress (on-premises, on request) |
| **HIPAA / FedRAMP** | Yes / Yes (Moderate, expanding to High) | No / No |
---
## Platform architecture and philosophy
Both platforms start from a strong architectural conviction, and those convictions point in opposite directions on almost every axis that matters.
### Dynatrace: OneAgent, Grail, and Smartscape, depth and automation with a proprietary bill
OneAgent installs on each host, auto-discovers running processes, and injects instrumentation at runtime, feeding a Smartscape topology that maps every dependency in real time and a Grail data lakehouse that holds logs, traces, metrics, and events together for schema-on-read querying through DQL. Davis reasons over that single topology, which is what lets it produce deterministic root cause across an entire system with no manual correlation. The Dynatrace Platform Subscription meters that automation across memory-GiB-hours, GiB scanned, and per-capability usage, so the bill reflects host memory, data volume, and how hard you investigate all at once. There is no hard cap on that spend: Dynatrace provides alerting when ingest crosses a threshold, but nothing stops the meter automatically. Managed self-hosting is available, but it remains a licensed proprietary deployment, not source-available software.
### Uptrace: OTLP-only ingestion on ClickHouse, with a hard cap and a free self-hosted path
Uptrace accepts data exclusively via OTLP, stores it in ClickHouse, and surfaces traces, metrics, and logs through one unified interface, with no proprietary agent and no vendor-specific SDK beyond the standard OTel libraries. That exclusivity is a stronger OTel commitment than most vendors make, including Dynatrace, which supports OTel but still treats OneAgent as the primary path. The v2.0 release brought JSON-based span storage for 5 to 10x faster queries, real-time transformation rules that filter or enrich telemetry before it hits storage, and multi-project support. The hard budget cap is the feature Dynatrace has no equivalent for: set a monthly ceiling, and Uptrace guarantees it never bills above that amount, dropping data rather than producing a surprise invoice. The free Community Edition on GitHub, licensed AGPL, runs full-featured with no data limits and no feature restrictions, so a team with the operational appetite for ClickHouse and PostgreSQL gets a production-grade backend for the cost of their own infrastructure.
The philosophical split is total. Dynatrace centralizes proprietary depth and automation in exchange for a consumption bill with no ceiling. Uptrace centralizes openness and cost predictability in exchange for a narrower, less automated product.
| Architectural factor | Dynatrace | Uptrace |
|---|---|---|
| Data storage | Grail (Dynatrace-hosted lakehouse) | ClickHouse + PostgreSQL |
| Instrumentation | OneAgent (auto-inject) or OTel | OTLP only (no proprietary agent) |
| Query interface | DQL (powerful, proprietary) | ClickHouse SQL + PromQL |
| Pricing mechanism | Consumption (memory, data, queries) | Data volume + datapoints (no seats) |
| Hard budget cap | No | Yes |
| Self-hosted option | Yes (Managed, licensed) | Yes (free, AGPL Community Edition) |
| Open source | No | Yes (Community Edition) |
| Learning curve | Steep | Low (single unified interface) |
[summary]
### Neither platform closes the incident loop
Dynatrace and Uptrace both detect and correlate, and both stop at alerting. Neither includes on-call scheduling with phone and SMS delivery or customer-facing status pages. Better Stack connects detection to response, so an alert becomes a paged responder, an incident timeline, and a status update in one platform.
**From heartbeat monitoring to incident timelines to status pages, one platform for the whole reliability lifecycle.** [Start free.](https://betterstack.com)
[/summary]
---
## APM and distributed tracing
This is the category where the gap is smallest, and it's worth being direct about that: both are genuinely serious APM products, even though the pricing gap between them is enormous.
### Dynatrace: PurePath, method-level depth with automatic topology enrichment
PurePath follows a transaction from the browser through every service and database call to the exact method responsible for the latency, with thread-level CPU and memory attribution, and Smartscape enriches every trace with topology automatically. Coverage extends to any host running OneAgent, including services nobody explicitly instrumented, which Uptrace's OTLP-only model cannot match. The familiar qualification applies: trace queries on the pay-per-query model carry GiB-scanned charges, so heavy investigation is metered.
### Uptrace: OTel-native tracing with fast, high-cardinality ClickHouse queries
Uptrace's exclusive OTLP ingestion means switching to it from another OTel-instrumented backend is a config change in your collector, not a re-instrumentation project. The v2.0 JSON-based span storage lets you query against any span attribute without pre-indexing, which matters for high-cardinality ad-hoc investigation, and flame graphs, RED-metric service maps, and p50/p90/p99 latency views are all present. The real limitation is coverage: every service needs OTel SDK instrumentation, so in a polyglot environment with dozens of services at different adoption stages, gaps appear wherever instrumentation hasn't reached yet. Dynatrace's OneAgent instruments regardless of whether anyone has touched the code. Uptrace also has no frontend APM at all: no RUM, no session replay, and no way to correlate a slow page load with a backend trace inside the product.
| APM / tracing | Dynatrace | Uptrace |
|---|---|---|
| Instrumentation | OneAgent (auto-inject) or OTel | OTel SDKs only (OTLP-only ingestion) |
| Code-level profiling | Yes (PurePath, method-level) | No |
| Coverage of uninstrumented services | Yes (OneAgent) | No (requires OTel SDK per service) |
| High-cardinality span queries | Yes (metered on pay-per-query) | Yes (v2.0 JSON storage, included) |
| Frontend-to-backend correlation | Yes (topology-aware) | No (no RUM) |
| Trace query cost | GiB-scanned on pay-per-query | Included in data pricing |
| Self-hosted option | Yes (Managed, licensed) | Yes (free) |
[summary]
### Tracing without a per-host memory bill or a query meter
Dynatrace meters trace queries and prices APM by host memory, and Uptrace requires OTel instrumentation on every service it sees. Better Stack's eBPF-based tracing captures HTTP, gRPC, and database traffic at the kernel level with zero code changes, priced purely by data volume, with an AI SRE that investigates root cause automatically when an incident fires.
**Full-fidelity distributed tracing from every service, priced by volume with no surprises.** [Explore Better Stack tracing.](https://betterstack.com/tracing)
[/summary]
---
## Log management
Both platforms make ingested logs fully searchable, but the cost gap here is one of the largest in this comparison.
Dynatrace ingests logs at $0.20/GiB into Grail, where schema-on-read removes upfront index and parser work, and DQL parses on read while enriching each line with Smartscape topology, so a log entry arrives already connected to the trace and host it came from. The recurring trade applies: pay-per-query meters each scan at $0.0035/GiB, while the bundled-queries plan removes that at roughly 28 times the retention price.
Uptrace stores logs in ClickHouse via OTLP, correlates them automatically with traces through OTel context propagation, and queries them with ClickHouse SQL, at roughly $0.10/GB on the cloud tier with volume discounts and no scan fee. The v2.0 real-time transformation layer lets you drop noisy debug-level logs at ingestion before they hit storage, a cost lever Dynatrace's flat per-GiB model doesn't offer. What Dynatrace has that Uptrace doesn't is a genuinely mature analytics layer on top of that data, richer faceting across arbitrary structured attributes, and up to seven years of retention with no rehydration; Uptrace's retention is configurable but has no equivalent long-term default.
| Log management | Dynatrace | Uptrace |
|---|---|---|
| Ingest cost | $0.20/GiB | ~$0.10/GB (or free self-hosted) |
| Query cost | $0.0035/GiB-scanned or bundled | None |
| Analysis tooling | DQL (schema-on-read, topology-enriched) | ClickHouse SQL |
| Retention | Usage-based, up to 7 years | Configurable, no long-term default |
| Real-time ingestion filtering | Limited | Yes (v2.0 transformation layer) |
| Self-hosted | No | Yes (free) |
[summary]
### Log search with no query meter and no rehydration fee
Dynatrace meters log queries within a mature analytics layer, and Uptrace charges less per GB but with a thinner log-analysis product. Better Stack stores logs in one SQL-queryable warehouse with no query fees and no per-event charges, so every log you send stays searchable at a flat volume-based rate.
**Unified log management with SQL search, live tail, and no indexing surprises.** [See how it works.](https://betterstack.com/logs)
[/summary]
---
## Infrastructure monitoring
Dynatrace's reach here is genuinely category-leading. Uptrace's is real but narrower, scoped to what OTel exporters can report.
### Dynatrace: the broadest coverage in the category, weighted by host memory
Dynatrace covers cloud-native infrastructure and reaches into SAP, VMware Tanzu, and z/OS mainframe workloads, all mapped under one Smartscape topology, with Kubernetes monitoring correlated directly to the method-level APM traces of the services running on each pod. Full-Stack is billed per memory-GiB-hour, so a large-memory host costs proportionally more, and cloud integrations can pull in metrics you never explicitly enabled.
### Uptrace: datapoint-based metrics with Prometheus compatibility and no seat gate
Uptrace bills metrics per million ingested datapoints, and metric extraction lets you derive metrics automatically from structured log fields without pre-configuring extraction rules. More than 50 pre-built dashboards activate automatically for Kubernetes, PostgreSQL, MySQL, Redis, Nginx, and other common stacks, and Grafana datasource compatibility, as a Prometheus or Tempo source, lets teams with existing Grafana dashboards point them at Uptrace without rebuilding, a bridge Dynatrace doesn't offer. There is no equivalent to Smartscape's automatic topology mapping, and coverage is scoped to whatever OTel exporters report rather than the mainframe, SAP, and VMware reach Dynatrace has. Because there's no seat model, every engineer looking at infrastructure data costs nothing extra, which is the opposite of Dynatrace's access-gated-by-subscription-tier reality.
| Infrastructure monitoring | Dynatrace | Uptrace |
|---|---|---|
| Mainframe / SAP / VMware | Yes | No |
| Host-size pricing | Yes (memory-GiB-hours) | No (datapoint-based) |
| Topology mapping | Smartscape (automatic) | No |
| Grafana compatibility | Limited | Yes (Prometheus + Tempo datasource) |
| Pre-built dashboards | Yes | Yes (50+, auto-created) |
| Access model | Consumption-gated | No seats, no access gate |
[summary]
### Infrastructure metrics wired into the whole reliability workflow
Dynatrace prices infrastructure by host memory and Uptrace by datapoint volume, but neither connects those metrics to on-call and incident response. Better Stack does, with no per-host fees and no cardinality penalties, and infra metrics that sit alongside uptime monitors, on-call schedules, and incident timelines.
**Infrastructure monitoring connected to alerting, on-call, and incident management, all in one place.** [Get started free.](https://betterstack.com)
[/summary]
---
## Digital experience monitoring
This section is short because the gap is total, not a matter of maturity. Dynatrace carries a mature digital experience suite: web and mobile RUM, session replay that lets you watch what a user experienced before a bug, browser synthetics, and HTTP monitors, all correlated back to PurePath traces with code-level context, priced per session. **Uptrace has none of this.** No RUM, no session replay, no synthetic monitoring, by design rather than by roadmap gap. If digital experience monitoring is a requirement, this section settles the comparison in Dynatrace's favor outright, and for teams where it isn't a requirement, that's exactly the capability Uptrace's lower price isn't paying for.
---
## AI capabilities
The gap here is structural rather than a matter of one platform being ahead in a shared race. Dynatrace has a genuine, mature AI story. Uptrace has none, and isn't trying to build one.
### Dynatrace: Davis, deterministic root cause since 2017, extended with agents and MCP
Davis is a deterministic causal engine, not a pattern-matcher. It runs fault-tree analysis across the Smartscape topology, folding correlated events into a single root-cause problem and tracing a bad deployment through the dependency graph to the user-facing symptom with reproducible reasoning. On top of it, Dynatrace Assist turns natural language into DQL, an SRE Agent investigates alerts autonomously, and AutomationEngine wires detection to remediation. The MCP server is generally available in remote and local versions, connecting Claude, Cursor, and similar tools to your data, with the caveat that MCP queries run against Grail and incur GiB-scanned charges.
### Uptrace: alerting, and nothing beyond it on the AI front
Uptrace sends alerts via email, Slack, webhook, and AlertManager, and the investigation from that point is entirely manual. There is no AI SRE, no MCP server, no natural language query interface, and no autonomous investigation of any kind. The platform's positioning is explicit about this: it aims to be a lean, cost-efficient observability backend, not an AI-augmented operations platform, and that scope boundary is honest rather than a gap waiting to close. For teams that have leaned into AI-assisted development workflows, the absence of an MCP server is a real, practical limitation: there is no way to point Claude Code or Cursor at Uptrace data directly, and every investigation means opening the Uptrace UI.
| AI capability | Dynatrace | Uptrace |
|---|---|---|
| Root cause engine | Davis (deterministic, topology-aware, GA since 2017) | No |
| Autonomous investigation | SRE Agent (agentic on Davis) | No |
| Natural language querying | Dynatrace Assist (GA) | No |
| MCP server | GA (remote + local) | No |
| Automated remediation | AutomationEngine | No |
| AI investment | Mature, ongoing | None; explicitly out of scope |
[summary]
### AI investigation that also drives the response
Davis reasons deterministically across your whole system, and Uptrace has no AI layer at all. Better Stack's AI SRE activates autonomously during an incident and delivers its hypothesis into a live incident with the responder already notified, included in the platform rather than metered separately.
**Autonomous root cause investigation connected to on-call, incidents, and status pages.** [See the AI SRE.](https://betterstack.com)
[/summary]
---
## Security, compliance, and deployment
Dynatrace has a genuine runtime application security product built on OneAgent's process-level visibility: Runtime Vulnerability Analytics detects which vulnerable libraries are actually loaded in running production processes and whether the vulnerable code paths are reachable, prioritizing by real exposure rather than raw CVSS score. Runtime Vulnerability Analytics and Runtime Application Protection run $13/month each per 8 GiB host, and Security Posture Management at $5/month per host checks compliance against CIS, NIST, DORA, and HIPAA, with FedRAMP and defense-adjacent certifications like IRAP, TISAX, and FIPS 140-3 on top.
Uptrace has no application security product, and its compliance story is architectural rather than certification-driven: the free self-hosted Community Edition means telemetry never leaves your network if you don't want it to, EU-based Uptrace Cloud runs in Hetzner's German data centers with Finnish backups and is GDPR-compliant by design, and managed on-premises installations are available from around $1,000/month excluding hosting. SOC 2 is available on request for on-premises customers but is still in progress generally, and HIPAA and FedRAMP are not available at any tier. For regulated industries that specifically require those certifications, Dynatrace is the only viable option between the two.
| Security and compliance | Dynatrace | Uptrace |
|---|---|---|
| Runtime application security | Yes (vuln + protection + posture) | No |
| Air-gapped deployment | Yes (Managed, licensed) | Yes (self-hosted, free) |
| SOC 2 Type II | Yes | In progress (on-premises, on request) |
| HIPAA | Yes | No |
| FedRAMP | Yes (Moderate, expanding to High) | No |
| GDPR | Yes | Yes (EU data centers by design) |
| Grafana compatibility | Limited | Yes (Tempo + Prometheus datasource) |
---
## Pricing comparison
The two pricing models could hardly be more different in shape. Dynatrace meters host memory, data volume, and query behavior with no ceiling. Uptrace meters data volume alone, with no seats and a hard cap that actually stops the bill.
Dynatrace's Full-Stack tier runs roughly $58/month per 8 GiB host, and a 64 GiB host runs closer to $467/month for the same coverage, because pricing is per memory-GiB-hour. A 100-host deployment averaging 8 GiB lands around $5,800/month for infrastructure and APM alone, before logs, RUM, or security, and before the minimum annual commitment reported around $24,000/year.
Uptrace Cloud starts at $30/month for 50GB of span storage and 10GB of log storage, with pay-as-you-go rates around $2/GB for spans, $1/GB for logs, and metrics billed per million datapoints after an April 2026 pricing update that moved metrics from active-timeseries to datapoint-based billing. Volume discounts apply automatically as usage grows. There are no per-host and no per-user fees at any tier, and the free self-hosted Community Edition removes the cloud bill entirely for teams willing to run ClickHouse and PostgreSQL themselves. Uptrace's own published comparison puts a large 150-engineer, 225-host deployment at roughly $2,039/month, against $24,635/month for New Relic at the same profile, a gap driven almost entirely by the absence of seat costs; the same shape of gap holds against Dynatrace's host-memory-weighted model, though Dynatrace's number would vary more with host size specifically.
The honest asymmetry works both ways. Uptrace's total buys no infrastructure breadth beyond OTel exporters, no AI, no RUM, and no application security, none of which Dynatrace's higher number can be separated from. Dynatrace's total buys real automation and depth that a lean, self-hostable backend was never built to provide. Model your host count, host memory profile, and how much of Dynatrace's automation you'd actually use before comparing the two numbers directly.
| Pricing factor | Dynatrace | Uptrace |
|---|---|---|
| Free tier | 15-day trial | Yes (cloud + unlimited free self-hosted) |
| Cost anchored to | Host memory + consumption | Data volume + datapoints |
| Per-user fee | No (but Full-Stack indirectly gates via cost) | No |
| Host-size sensitivity | High (memory-GiB-hours) | None |
| Hard budget cap | No | Yes |
| Minimum commitment | ~$24,000/year reported | None |
| Self-hosted option | Yes (Managed, licensed) | Yes (free, AGPL) |
---
## What each platform genuinely lacks
**Dynatrace gaps worth knowing:**
1. No hard budget cap; a misconfigured integration or aggressive investigation can produce unexpected overage.
2. Memory-weighted Full-Stack pricing penalizes large-memory hosts heavily.
3. No free or open-source path; the self-hosted Managed deployment is a licensed proprietary product.
4. Steep learning curve, with reviewers flagging dense dashboards and onboarding effort.
5. Minimum annual commitment excludes small teams entirely.
6. No customer-facing status pages and no native on-call with phone or SMS delivery.
7. No Grafana datasource compatibility for teams with existing dashboard investments.
**Uptrace gaps worth knowing:**
1. No AI of any kind: no root cause engine, no MCP server, no natural language querying.
2. No digital experience monitoring: no RUM, no session replay, no synthetic monitoring.
3. No infrastructure breadth beyond OTel exporters; no mainframe, SAP, or VMware coverage.
4. No application security product.
5. Every service requires OTel SDK instrumentation; no auto-instrumentation path for uninstrumented services.
6. No incident management, on-call scheduling, or phone/SMS delivery.
7. No HIPAA or FedRAMP certification, and SOC 2 remains in progress.
---
## Final thoughts
This comparison resolves cleanly once you separate what each platform is optimizing for, because neither one is quietly trying to become the other.
Reach for **Dynatrace** when your environment demands depth and automation that a lean backend cannot provide. If you need **method-level PurePath profiling, deterministic Davis root cause across a complex topology, coverage that spans SAP, VMware, and the mainframe, and runtime application security**, Uptrace is not built to compete and Dynatrace stands alone in this pair. The cost is real: **a consumption model with no ceiling, memory-weighted pricing that punishes large hosts, and the steepest learning curve of the two.**
Reach for **Uptrace** when your stack is already OpenTelemetry-instrumented and cost predictability, data ownership, or both are first-order concerns. **Because Uptrace is exclusively OTLP-native, switching to it is a config change, not a re-instrumentation project**, and its **hard budget cap actually stops the meter rather than just alerting on it**. The **free, fully-featured, self-hosted Community Edition** means a team with the operational appetite for ClickHouse can run a production-grade backend for the cost of its own infrastructure, and the **absence of a seat model** means growing your engineering team doesn't grow your bill. The trade is scope: **no AI, no digital experience monitoring, no infrastructure breadth beyond what OTel reports, and no application security.**
The clarifying question is not which platform is better but how much of the observability stack you want to own versus rent, and how much automated depth your organization actually needs day to day. **If you want maximum automation and are prepared to pay a consumption bill with no ceiling for it, Dynatrace is the answer. If you want an open, self-hostable, cost-predictable backend for an OTel-instrumented stack and don't need AI or DEM, Uptrace is the answer.** Model your real telemetry volume and host profile against both, and be honest about which of Dynatrace's automated capabilities you'd actually use before paying for the rest of them.
[summary]
### One thing neither platform covers: the full reliability layer
Neither Dynatrace nor Uptrace includes uptime monitoring, on-call scheduling with phone and SMS, incident management, and customer-facing status pages as a unified product. Better Stack brings all of that together with logs, metrics, and traces, with usage-based pricing and no per-host or per-query surcharges.
**The full reliability lifecycle in one place. Start free, no credit card required.** [Try Better Stack.](https://betterstack.com)
[/summary]