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Datadog vs Observer GigaStor 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 Network Monitoring Software
3rd
Average Rating
8.6
Reviews Sentiment
6.9
Number of Reviews
211
Ranking in other categories
Application Performance Monitoring (APM) and Observability (1st), IT Infrastructure Monitoring (2nd), Log Management (3rd), Container Monitoring (2nd), Cloud Monitoring Software (2nd), AIOps (1st), Cloud Security Posture Management (CSPM) (5th), AI Observability (1st)
Observer GigaStor
Ranking in Network Monitoring Software
89th
Average Rating
9.0
Reviews Sentiment
8.1
Number of Reviews
7
Ranking in other categories
Network Troubleshooting (14th), Network Packet Broker (NPB) (11th)
 

Mindshare comparison

As of January 2026, in the Network Monitoring Software category, the mindshare of Datadog is 2.4%, down from 3.7% compared to the previous year. The mindshare of Observer GigaStor is 0.4%, up from 0.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Network Monitoring Software Market Share Distribution
ProductMarket Share (%)
Datadog2.4%
Observer GigaStor0.4%
Other97.2%
Network 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.
Jeroen-Dubbelman - PeerSpot reviewer
Director at Bitrate
Aids significantly in the threat-hunting process and provides a score-based evaluation of user experience
There are many valuable features, but understanding end-user response times stands out. It provides a score-based evaluation of user experience, helping customers quickly pinpoint whether issues originate from the network, server, client, or application. Additionally, it facilitates in-depth analysis of application dependencies. The retrospective network analysis capability of Observer GigaStor has been beneficial. It's a pivotal feature for network performance solutions. However, I prefer to consider the entire solution suite - GigaStor, along with GigaFlow and Apex - for comprehensive network visibility and monitoring. So, I prefer to integrate all three solutions to provide the best visibility. They complement each other well, with Apex aggregating and correlating data from both GigaStor and GigaFlow to enhance environmental understanding and troubleshooting efficiency.

Quotes from Members

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

Pros

"The fact that everything is under a single pane of glass is really valuable, as developers don't have to spend their time copying correlation IDs across tools to find what they need."
"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."
"The performance of Datadog is good."
"The ease of use allowed me to get up to speed with log management since it's my first time using Datadog."
"Profiling has been made easier."
"Datadog has impacted our organization positively because the general feeling is that it's superior to the ELK stack that we used to use, being significantly faster in searching and filtering the information down, as well as providing links to our search criteria that our development teams and cloud operations teams can use to look at the same problems without having to set up their own search and filter criteria."
"The most valuable feature is the dashboards that are provided out of the box, as well as ones we were able to configure."
"Having a wealth of information has helped us investigate outages, and having historical data helps us tune our system."
"This solution allows us to see exactly what is going on in the network and we can very quickly solve issues with users."
"I also have the ability to see an application's performance, to see what's going on, why a network is slow, why this program for this user is experiencing a delay or some network issue"
"The ability to capture packets. It is not only for monitoring. That is very important for a company that wants to keep an eye on the packets, the transactions, the flows..."
"It's able to capture packets and, after a long time, you can come and use that information; to check, to analyze - everything you would want to do. So it's very good and helpful if you want to protect your data. It is stored in a certain place where you can access it every time you want to analyze it."
"It can help to write your rules, organize firewalls, your block, and also your protocols and IP address to come in or out of your network."
"There are many valuable features, but understanding end-user response times stands out. It provides a score-based evaluation of user experience, helping customers quickly pinpoint whether issues originate from the network, server, client, or application. Additionally, it facilitates in-depth analysis of application dependencies."
 

Cons

"I would love to see more metrics or analytics in IoT devices."
"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."
"Another issue that I have is with the search syntax, it could be simpler and it feels like there are too many ways to do the same things."
"One area where I was really looking for improvement was the CSPM product line. I had really wanted to have team-level visibility for findings, since the team managing the resources has much more context and ability to resolve the issue, as the service owner. However, this has been added to the announcement in a recent keynote."
"There could be more easily identifiable documentation on how to find different things on the platform."
"Sometimes it’s difficult to customize certain queries to find specific things, specifically with the logging solution."
"There is always room for improvement when dealing with cloud-based technologies. Mainly, I would say, it's just increasing our offerings to attract various other types of industries and businesses across more fields."
"Datadog has a lot of documentation, but a lot of that documentation assumes you know how the service works, which can lead to confusion."
"I would like to have more than 4TB of storage available in the portable version of this solution."
"GigaStor feeds into Apex. So, the area where there could be improvement would be in artificial intelligence. For example, the incorporation of more advanced machine learning or AI capabilities could enhance its functionality."
"Maybe the graphical user interface could be simplified to allow people to use it more easily. It's already good, but they can work more on it to make it even easier."
"Graphics need improvement. Because a lot of the information there you have to input first in some case to have full potential. It could be more automated."
 

Pricing and Cost Advice

"The solution's pricing depends on project volume."
"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 costs the same amount it would if we were hosting it ourselves, so we are incredibly happy with the cost."
"The solution is fairly priced but history and log storage can get costly depending on your needs."
"It has a module-based pricing model."
"This solution is budget friendly."
"Pricing is somewhat affordable compared to other solutions but in order to really lower the costs of other products you need to plan very carefully your resources usage, otherwise, it can get expensive real quick."
"It depends on the requirements you have. There are three types of license. There's the updates license, the work group license, and the workstation license."
"It's quite expensive."
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Top Industries

By visitors reading reviews
Financial Services Firm
14%
Computer Software Company
12%
Manufacturing Company
8%
Healthcare Company
6%
Financial Services Firm
17%
Computer Software Company
11%
Manufacturing Company
8%
Wholesaler/Distributor
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business80
Midsize Enterprise46
Large Enterprise99
By reviewers
Company SizeCount
Small Business5
Large Enterprise3
 

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 do you like most about Observer GigaStor?
There are many valuable features, but understanding end-user response times stands out. It provides a score-based evaluation of user experience, helping customers quickly pinpoint whether issues or...
What is your experience regarding pricing and costs for Observer GigaStor?
I would rate the pricing a ten out of ten. It's quite expensive.
What needs improvement with Observer GigaStor?
GigaStor feeds into Apex. So, the area where there could be improvement would be in artificial intelligence. For example, the incorporation of more advanced machine learning or AI capabilities coul...
 

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
Cisco Systems, Hawaiian Telecom, Renown Health, State of Nevada, U.S. Department of Veteran Affairs, Allstate Insurance, Jack Henry & Associates, United States Airforce, US Bank, Blue Cross Blue Shield of Minnesota, Texas Tech University Health Sciences Center, Chicago Board Options Exchange
Find out what your peers are saying about Datadog vs. Observer GigaStor and other solutions. Updated: December 2025.
881,176 professionals have used our research since 2012.