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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 (2nd), AIOps (1st), Cloud Security Posture Management (CSPM) (5th), AI Observability (1st)
Unomaly
Ranking in Cloud Monitoring Software
39th
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 January 2026, in the Cloud Monitoring Software category, the mindshare of Datadog is 6.7%, down from 11.4% 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 (%)
Datadog6.7%
Unomaly0.2%
Other93.1%
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

"We integrate our application logs. It is great to be able to tie our metrics and our traces together."
"The real-time data helps us make informed decisions and optimize our operations, ultimately enhancing our overall efficiency and performance."
"Being able to filter requests by latency is invaluable, as it provides immediate insight into which endpoints require further analysis and optimization."
"The web app has a real-time support chat window in which a support engineer is chatting with you within a minute."
"The visibility into our network has allowed for quick diagnosis of failures, identification of underutilized or over-utilized resources, and allowed for cloud cost optimization opportunities."
"Watchdog is a favorite feature among a lot of the devs. It catches things they didn't even know were an issue."
"Datadog has positively impacted my organization by shortening our time to resolve incidents because it's a central place for getting all the data that we need for troubleshooting."
"Our primary alerts, based on metrics and synthetic transactions, are the most used and relied upon for decreased MTTA/MTTR across all of our platforms. This is followed by deep log analysis that enables us to quickly and easily get to a preliminary root cause that someone on the infrastructure, platform or development teams can take and focus their attention on the precise target that Datadog revealed as the issue to be remediated."
"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

"They need to offer better/more customization on what logs we get and making tracing possible on Edge runtime logs is a real requirement."
"While it’s powerful, the interface can feel cluttered and overwhelming for new users."
"The solution should provide alerts for cloud outages."
"I think Datadog can be improved by continually finding errors and making things easy to see and customize."
"I found the solution to be stable, I did not experience any bugs or glitches. However, some of the managing team did."
"The cost is pretty high."
"I would appreciate seeing it as an app or mobile app for quicker issue tracking."
"The real issue with this product is cost control."
"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 solution is fairly priced but history and log storage can get costly depending on your needs."
"My advice is to really keep an eye on your overage costs, as they can spiral really fast."
"Pricing and licensing are reasonable for what they give you. You get the first five hosts free, which is fun to play around with. Then it's about four dollars a month per host, which is very affordable for what you get out of it. We have a lot of hosts that we put a lot of custom metrics into, and every host gives you an allowance for the number of custom metrics."
"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 cost is high and this can be justified if the scale of the environment is big."
"The solution's pricing depends on project volume."
"The price of Datadog is reasonable. Other solutions are more expensive, such as AppDynamics."
"Our licensing fees are paid on a monthly basis."
Information not available
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Top Industries

By visitors reading reviews
Financial Services Firm
14%
Computer Software Company
12%
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

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
ESL  VasakronanTurtle Entertainment 
Find out what your peers are saying about Zabbix, Datadog, Microsoft and others in Cloud Monitoring Software. Updated: December 2025.
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