RMM Pricing vs. Real Diagnostics: What Are You Actually Paying For?

The RMM market has consolidated around two distinct pricing philosophies: pay per device managed, or pay per technician and manage unlimited devices. Which one wins depends almost entirely on your device-to-technician ratio. Vendors are generally banking on you not running the math before signing.

This article breaks down how the major platforms actually price their offerings, what features are included in the base price versus gated behind add-ons or higher tiers, and where ET Ducky fits if your primary pain is understanding why Windows machines misbehave rather than just knowing that they are.

The Two Pricing Models

Per-device pricing is used by NinjaOne, ConnectWise RMM, Datto RMM, and Kaseya VSA. Costs scale linearly with your fleet size and most vendors offer volume discounts at thresholds of roughly 100, 500, and 1,000+ endpoints. The math is transparent once you have a quote, but getting that quote requires a sales conversation, since none of these vendors publish their rates.

Per-technician pricing is used by Atera and Syncro. You pay per seat regardless of endpoint count, which makes it the better model as your device-to-tech ratio grows. A team of 3 technicians managing 1,000 endpoints pays the same as 3 technicians managing 100. The calculator above shows this inflection point clearly: drag the agents slider to the right and watch Atera and Syncro become cheaper relative to the per-device platforms.

ET Ducky uses a hybrid: a flat monthly subscription covers a base query allowance and 20 free managed agent seats per subscribed user. Additional agents are priced at $5/month on shared infrastructure, dropping to $4, $3, and $2 as you scale into dedicated deployment tiers. Data retention is a separate per-agent add-on.

Platform Pricing: What's Included and What Costs Extra

Feature Matrix: What's in the Base Price

The table below shows what's included in each platform's standard pricing versus what requires an add-on purchase or a higher tier. "Add-on" means the feature exists but costs extra. "Tier" means it's included but only at a higher subscription level.

ET Ducky Data Retention Tiers

Data retention in ET Ducky controls how long cloud-stored ETW events, health metrics, correlation analyses, and session data are kept before automatic purge. The 14-day default is free for all organizations. The add-on tiers are billed per managed agent per month across your entire fleet.

Annual billing saves 15% on retention costs. The calculator above factors this in when you select the annual billing option.

What Price Can't Buy: The Diagnostic Gap

Every platform in the table above can tell you that CPU hit 90% on a server. None of them can tell you what happened at the kernel level to cause it, regardless of price or tier. That's not a feature omission that gets added in the next release; it's an architectural difference in what data the agent collects.

Traditional RMM agents collect WMI health counters every 30–60 seconds and forward Event Log entries. WMI gives you sampled snapshots. Event Logs tell you what applications chose to record. Neither captures the continuous, microsecond-resolution kernel event stream that shows you thread states, memory allocation sequences, I/O latency attribution, and the causal chain between system events.

ETW (Event Tracing for Windows) is the kernel's own telemetry infrastructure. A busy Windows server generates 10,000–100,000 ETW events per second, which is impractical to ship anywhere. ET Ducky processes this stream locally on the agent, correlates related events into compact diagnostic summaries, filters out PII before anything leaves the machine, and delivers 99.6% bandwidth reduction while preserving the information needed to explain why something happened rather than just that it happened.

Instead of "CPU exceeded 90% on SERVER-12," you get "CPU exceeded 90% on SERVER-12 because the .NET garbage collector ran a full Gen 2 collection lasting 4.2 seconds, triggered by WorkerService.exe exceeding its 2 GB heap limit."

This isn't available from NinjaOne, ConnectWise, Datto, Kaseya, Atera, or Syncro at any price point. The agents these platforms run don't subscribe to ETW providers. The diagnostic depth simply doesn't exist in the data they collect.

Where ET Ducky Fits

There are two common deployment patterns.

As a complement to an existing RMM. Keep your current platform for patch management, software deployment, backup monitoring, macOS/Linux coverage, and PSA integration. Add ET Ducky to your Windows endpoints specifically for diagnostic depth. When an alert fires in NinjaOne, use ET Ducky's AI-analyzed ETW data to understand the root cause instead of spending time in remote sessions clicking around. The tools don't overlap: your RMM manages the fleet, ET Ducky explains what's happening inside Windows machines when something is wrong.

As a standalone for Windows-only environments. If your fleet is entirely Windows and you don't need patch automation, macOS management, or backup monitoring from the same tool, ET Ducky covers health monitoring, alerting, remote desktop, and approved script execution, plus the diagnostic layer no traditional RMM provides. For Windows-only shops, the total cost is often well below a full-featured RMM once you factor in the free seat allowance.

The Bottom Line

If you haven't run your actual endpoint count and technician count through a cost comparison, the calculator above is the fastest way to see where the per-device and per-technician models cross over for your situation. At low device-to-tech ratios, per-device platforms often win. At high ratios, Atera and Syncro's unlimited-endpoint model becomes substantially cheaper.

What the cost comparison can't show is diagnostic quality. All seven platforms in this comparison can tell you a server is slow. Only one can tell you why, at the kernel level, with enough specificity to fix the root cause rather than patch around it. Whether that's worth adding to your stack depends on how much time your team currently spends staring at high CPU graphs wondering what's actually happening inside the machine.