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Datadog vs Unomaly comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Jan 25, 2026

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Categories and Ranking

Datadog
Ranking in Cloud Monitoring Software
2nd
Average Rating
8.6
Reviews Sentiment
6.9
Number of Reviews
211
Ranking in other categories
Application Performance Monitoring (APM) and Observability (1st), Network Monitoring Software (3rd), IT Infrastructure Monitoring (2nd), Log Management (3rd), Container Monitoring (1st), AIOps (1st), Cloud Security Posture Management (CSPM) (5th), AI Observability (1st)
Unomaly
Ranking in Cloud Monitoring Software
38th
Average Rating
7.0
Reviews Sentiment
2.4
Number of Reviews
1
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of February 2026, in the Cloud Monitoring Software category, the mindshare of Datadog is 6.5%, down from 11.1% compared to the previous year. The mindshare of Unomaly is 0.2%, up from 0.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Cloud Monitoring Software Market Share Distribution
ProductMarket Share (%)
Datadog6.5%
Unomaly0.2%
Other93.3%
Cloud Monitoring Software
 

Featured Reviews

Dhroov Patel - PeerSpot reviewer
Site Reliability Engineer at Grainger
Has improved incident response with better root cause visibility and supports flexible on-call scheduling
Datadog needs to introduce more hard limits to cost. If we see a huge log spike, administrators should have more control over what happens to save costs. If a service starts logging extensively, I want the ability to automatically direct that log into the cheapest log bucket. This should be the case with many offerings. If we're seeing too much APM, we need to be aware of it and able to stop it rather than having administrators reach out to specific teams. Datadog has become significantly slower over the last year. They could improve performance at the risk of slowing down feature work. More resources need to go into Fleet Automation because we face many problems with things such as the Ansible role to install Datadog in non-containerized hosts. We mainly want to see performance improvements, less time spent looking at costs, the ability to trust that costs will stay reasonable, and an easier way to manage our agents. It is such a powerful tool with much potential on the horizon, but cost control, performance, and agent management need improvement. The main issues are with the administrative side rather than the actual application.
reviewer2771775 - PeerSpot reviewer
Consulting Head at a outsourcing company with 5,001-10,000 employees
Has improved error detection significantly but still needs deeper integration with intelligent automation
I have been using Unomaly or LM Envision by LogicMonitor for a year for internal purposes. I personally don't use metrics to evaluate Unomaly's performance as I have a team who handles that aspect. The endgame has moved towards agentic AI. Two years back, it was supposed to be the endgame with ML and prediction anomaly. The world has moved on. Having Unomaly, even the best anomaly doesn't make too much of a difference. The endgame is now about the metrics of autonomy rather than anomaly. What is the degree of autonomy? What is the return on autonomy? Those are the metrics I'm more interested in than just having the anomaly. The world order has shifted, and the KPIs have shifted. They already have Gen AI and agentic AI features, but we haven't used them so far. I will continue to use it in the future for now as it's only been a year. We don't want to change anything internally for now. I would recommend Unomaly to other customers because anybody using observability can and should use Unomaly in the new world. I can't think of any types of companies I would not recommend it to because observability cannot exist without Unomaly nowadays. On a scale of 1 to 10, I rate Unomaly a seven.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"This spectrum of solutions has allowed us to track down bugs faster and more rapidly, which allows us to limit revenue lost during downtime."
"The technology itself is generally very useful and the interface is great."
"Sometimes it's more user friendly for development teams. There are some parts of Datadog that are more understandable for development teams. For example, the APM in Datadog works more manually and works like the tools in New Relic or Grafana, or Elastic. It is easier to understand for software development teams."
"It lets us react more quickly to things going wrong. Whereas before, it might have been 30 minutes to an hour before we noticed something going on, we will know within a minute or two if something is off, which will let us essentially get something back up and running faster for our customers, which is revenue."
"Since using Datadog, it has positively impacted our organization by giving us a one-stop shop for multiple applications and services that we can analyze in one spot."
"Datadog has impacted my organization positively as this is our main observability tool when it comes to monitoring services, traces, and all resources within key services."
"The most valuable feature I have found is the elastic container service."
"The monitoring functionality, in general, and tagging infrastructure are great."
"Unomaly's anomaly detection capabilities contribute to maintaining system reliability; we cannot find all errors humanly, we cannot configure every possible threshold, and in the new world of intelligence and AI, we need to have this intelligent way of finding out the anomalies."
"Unomaly's anomaly detection capabilities contribute to maintaining system reliability; we cannot find all errors humanly, we cannot configure every possible threshold, and in the new world of intelligence and AI, we need to have this intelligent way of finding out the anomalies."
 

Cons

"More granular control over dashboard sharing. Timeboard sharing."
"It could probably be a little bit of a better user experience."
"We need more integration functionality, including certain metrics integration."
"The ease of implementation was a bit difficult for us for the database servers where we have different kinds of databases. We needed different kinds of agents to be installed, and that was a bit tricky for us."
"Delta traces on the Golang profiler are extremely expensive concerning memory utilization."
"Datadog's roadmap can be a bit unpredictable at times."
"I'm not sure what kind of features are in the roadmap right now, but I encourage the development of features for defining your organization, and allowing the visibility of what kind of metrics you can get. Those features would be really useful for us."
"I often have issues with the UI in my browser."
"Having Unomaly, even the best anomaly doesn't make too much of a difference."
"Having Unomaly, even the best anomaly doesn't make too much of a difference."
 

Pricing and Cost Advice

"It costs the same amount it would if we were hosting it ourselves, so we are incredibly happy with the cost."
"Our licensing fees are paid on a monthly basis."
"Licensing is based on the retention period of logs and metrics."
"This solution is budget friendly."
"Datadog does not provide any free plans to use the solution. When I start with a proof of concept it would be sensible to have a free plan to test the tool and check whether it fits the requirements of the project. Before the production stage, it is always good to have a free plan with some limited features, number of requests, or logs."
"They prefer monthly subscriptions."
"I am not satisfied with its licensing. Its payment is based on the exported data, and there was an explosion of the data for three or four weeks. My customer was not alerted, and there was no way for them to see that there has been an explosion of data. They got a big invoice for one or two months. The pricing model of Datadog is based on the data. The customer was quite surprised about not being alerted about this explosion of data. They should provide some kind of alert when there is an increase in usage."
"It has always scaled for us. Cost scales up too, but that is not necessarily a bad thing. It's reasonable for what they're providing."
Information not available
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Top Industries

By visitors reading reviews
Financial Services Firm
14%
Computer Software Company
11%
Manufacturing Company
8%
Healthcare Company
6%
No data available
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business80
Midsize Enterprise46
Large Enterprise99
No data available
 

Questions from the Community

Any advice about APM solutions?
There are many factors and we know little about your requirements (size of org, technology stack, management systems, the scope of implementation). Our goal was to consolidate APM and infra monitor...
Datadog vs ELK: which one is good in terms of performance, cost and efficiency?
With Datadog, we have near-live visibility across our entire platform. We have seen APM metrics impacted several times lately using the dashboards we have created with Datadog; they are very good c...
Which would you choose - Datadog or Dynatrace?
Our organization ran comparison tests to determine whether the Datadog or Dynatrace network monitoring software was the better fit for us. We decided to go with Dynatrace. Dynatrace offers network ...
What needs improvement with Unomaly?
We do not use its Contextual Insight feature. We haven't explored the LLM side. That part wasn't GA. They've recently launched it. The agentic AI feature has not been tried yet. I would need to che...
What is your primary use case for Unomaly?
The primary use cases for Unomaly involve all kinds of things. It's a rate anomaly, error anomaly, it could be anything. Any kind of anomalous pattern can be detected. Unomaly's anomaly detection c...
What advice do you have for others considering Unomaly?
I have been using Unomaly or LM Envision by LogicMonitor for a year for internal purposes. I personally don't use metrics to evaluate Unomaly's performance as I have a team who handles that aspect....
 

Comparisons

 

Overview

 

Sample Customers

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