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Datadog vs Unomaly comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Oct 19, 2025

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
7.0
Number of Reviews
209
Ranking in other categories
Application Performance Monitoring (APM) and Observability (1st), Network Monitoring Software (3rd), IT Infrastructure Monitoring (2nd), Log Management (3rd), Container Monitoring (2nd), 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 December 2025, in the Cloud Monitoring Software category, the mindshare of Datadog is 7.3%, down from 11.7% 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 (%)
Datadog7.3%
Unomaly0.2%
Other92.5%
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

"Datadog has helped my organization improve a lot of response time because we get alerts the minute it happens, which is our only means to reduce incident response time."
"We can handle debugging and find out why things are breaking in our applications."
"I find the greatest feature is being able to search across logs from various microservices."
"Real user monitoring has made triaging any possible bugs our users might face a lot easier."
"With Datadog I can look at the health of the technology stack and services."
"Datadog has positively impacted my organization by allowing for a more proactive response to issues whenever they occur."
"The most valuable aspect is for us to have everything in one place."
"It has a high-level insight into the infrastructure model of the application and provides important detailed data on the host and metrics, which is the main concern of our customers."
"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

"Delta traces on the Golang profiler are extremely expensive concerning memory utilization."
"The product can be improved by allowing the grouping of APIs to add variables. That way, any API with a unique ID could be grouped together."
"I would love to see support for front-end and mobile applications. Right now, it is mostly all back-end stuff. Being able to do some integration with our front-end products would be awesome."
"They should continue expanding and integrating with more third-party apps."
"It would be great if usage metrics were automatically created and we could create custom metrics, instead we ended up building some of our own stuff to track and alert on our own usage."
"In some ways, the tool has a pretty steep learning curve. Discovering the various capabilities available, then learning how to utilize them for particular use cases can be challenging."
"One area where the product could be improved is Application Performance Monitoring (APM)."
"If there were a more cost-effective manner of deploying the tool, we'd be more likely to adopt it more widely."
"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

"The price of Datadog is reasonable. Other solutions are more expensive, such as AppDynamics."
"While it is an expensive product, I would rate the pricing level at four out of five."
"​Pricing seems reasonable. It depends on the size of your organization, the size of your infrastructure, and what portion of your overall business costs go toward infrastructure."
"The pricing came up a bit compared to their competitors. It is not that the price has risen, but that the competitors have gone down. They keep adding more features that I would have expected to be baked in at a more nominal price. I have been increasingly dissatisfied with the pricing, but not enough to jump ship."
"The cost is high and this can be justified if the scale of the environment is big."
"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."
"The solution is fairly priced but history and log storage can get costly depending on your needs."
"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
13%
Manufacturing Company
7%
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 Enterprise97
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

No data available
 

Overview

 

Sample Customers

Adobe, Samsung, facebook, HP Cloud Services, Electronic Arts, salesforce, Stanford University, CiTRIX, Chef, zendesk, Hearst Magazines, Spotify, mercardo libre, Slashdot, Ziff Davis, PBS, MLS, The Motley Fool, Politico, Barneby's
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