New Relic suits engineering teams who want to get going without a sales call, with free access to the full platform, 800+ integrations and OpenTelemetry support. Dynatrace suits large organisations running complex cloud estates who want automatic topology mapping, causal AI and one data lakehouse. Neither is better for every team, so try both on real services before you commit.
One of these platforms lets an engineer sign up this afternoon and point it at production without speaking to anyone. The other asks you to start a trial or book a demo. It's a small difference at the front door, but it says a lot about who each one is built for, and it's where this comparison begins.
Both are large observability vendors covering APM, infrastructure, logs and digital experience. Where they split is in how they hold your data, how their AI reasons about problems and how much they want you building on their own model. To keep it readable, I'll call them the free-access platform and the lakehouse platform from here on.
Getting in the door
New Relic's home page says you can access the full platform for free with no credit card. That's rare at this end of the observability world, and it means a small team or a single engineer can find out how far the free access goes before anyone talks about contracts.
The lakehouse platform offers a free trial and a demo instead, with a usage-based model. It fits its pitch to large organisations, where a guided start with the vendor's team is normal and expected.
There's a second point under the surface. The lakehouse platform is built from its own named building blocks: Grail for storage, Smartscape for topology and OpenPipeline for ingestion, and its platform page shows its own custom query. It tells you it's designed around its own data model, rather than giving a plug-in-anything feel. You'll want to be comfortable with that before you commit a large estate to it.
Where your telemetry lives
This is the deepest difference between the two. The free-access platform pitches querying telemetry where it already sits, across warehouses and lakes, without moving the data, and adds federated logs. The vendor says the telemetry is analysed in real time.
The lakehouse platform stores data in Grail, which it calls a causal data lakehouse, and uses OpenPipeline to ingest and pre-process data on the way in. One approach leaves data in place and reaches out to it. The other pulls it into one store built for its AI. If your company already has a data warehouse strategy, that should weigh heavily in your choice.
Side-by-side snapshot
| Question | New Relic | Dynatrace |
|---|---|---|
| How do I start? | Full platform free, no credit card | Free trial or demo, usage-based model |
| Where does data live? | Queried in place across warehouses and lakes, with federated logs | Grail causal data lakehouse, fed by OpenPipeline |
| What does the AI do? | Autopilot, an SRE Agent for automated remediation and AI monitoring for models and agents | Dynatrace Intelligence: agentic operations on deterministic AI and causal context |
| How is topology shown? | Service maps, distributed tracing and eBPF network performance | Smartscape maps apps and infrastructure automatically |
| Can I build on it? | 800+ pre-built integrations and OpenTelemetry support | AppEngine for custom apps and automations |
| What extras are there? | Business Observability, cloud spend intelligence, SAP Monitoring, Security Rx | Threat Observability, Software Delivery, business events |
Two ideas of what AI should do in an incident
The free-access platform has three AI pieces: Autopilot, an SRE Agent for automated remediation, and a separate AI monitoring product for your own models and agents. That last one matters if your product calls large language models, because it watches the AI you run as well as the services around it.
The lakehouse platform leans on what it calls deterministic AI. The vendor says its Intelligence layer gives causal root cause, and it uses that to drive agentic action. The idea is that the AI follows cause and effect through the mapped estate rather than guessing from patterns. Ask for a walk-through on an incident from your own systems to see how that plays out.
Maps of your estate
Smartscape automatically maps how apps and infrastructure relate to each other, which is a big help in a sprawling cloud setup where nobody holds the full picture in their head. The free-access platform covers similar ground with service maps, distributed tracing and eBPF network performance in its APM listing. Both give you a map, but one builds it automatically as the foundation for its AI.
Building your own tools on top
If your engineers like to connect everything, the free-access platform lists 800+ pre-built integrations and supports OpenTelemetry. The lakehouse platform takes a different route with AppEngine, which lets teams build custom apps and automations directly on its platform. One opens outwards, the other invites you to build inside.
Both add extras beyond core monitoring. The free-access platform lists Business Observability, a cloud spend intelligence tool, SAP Monitoring and Security Rx. The lakehouse platform lists Threat Observability, Software Delivery and business events drawn from observability data. Check which list maps to work you'd otherwise buy separately.
Rivals worth a trial
For a broader view, our guide to the best observability tools covers more platforms, and the comparison of how Datadog stacks up against Dynatrace is a useful next read.
Want AI doing the heavy lifting in your marketing?
I build the systems that handle the boring 80 percent, so you get your week back. Done properly, with the human kept in.
Datadog
Best for: Cloud teams wanting many monitoring and security products in one place, with Bits AI agents and an MCP server across the platform.
Grafana Labs
Best for: Teams that prefer open source tooling, with native OpenTelemetry support and a Free Forever plan on Grafana Cloud.
Elastic Observability
Best for: Anyone already on Elastic, or wanting search-based analysis, with AI SRE agents and hosted, serverless or self-managed options.
Splunk Observability
Best for: Organisations already on Splunk, with infrastructure, APM and IT service intelligence plus a free edition for up to 15 hosts.
The verdict for engineering leads
Go with the free-access platform if you want to start without a sales call, see how far the free full-platform access takes you, and keep your data where it already sits with broad integrations and OpenTelemetry. Go with the lakehouse platform if you run a large, complex estate and want automatic topology mapping, causal AI and a single data lakehouse built for it. No feature list proves one is better for every team, so point both at real services and judge the results.
Do you make an observability or APM platform? Tool makers can ask to be considered for a featured place on this page.
Want your tool on this list? Featured spots and reviews here are paid partnerships. Here's how to partner with me.
Frequently asked questions
Is New Relic free to start?
Its home page says you can access the full platform for free with no credit card. Check the sign-up page for what the free access includes.
Does Dynatrace have a free option?
It offers a free trial and a demo, with a usage-based model, rather than a standing free tier.
What is Grail in Dynatrace?
Grail is its causal data lakehouse, where observability data is stored after OpenPipeline ingests and pre-processes it.
Which one supports OpenTelemetry?
The free-access platform lists OpenTelemetry support alongside 800+ pre-built integrations. The lakehouse platform leans on its own building blocks and AppEngine for custom work.
Can either monitor AI models and agents?
The free-access platform sells an AI monitoring product for models and agents, alongside its SRE Agent and Autopilot.
