Datadog is a monitoring service for IT, Dev and Ops teams who write and run applications at scale, and want to turn the massive amounts of data produced by their apps, tools and services into actionable insight.
$18
per month per host
Dynatrace
Score 8.4 out of 10
N/A
Dynatrace is an APM scaled for enterprises with cloud, on-premise, and hybrid application and SaaS monitoring. Dynatrace uses AI-supported algorithms to provide continual APM self-learning and predictive alerts for proactive issue resolution.
$0
per synthetic request
Splunk Observability Cloud
Score 8.4 out of 10
N/A
Splunk Observability Cloud aims to enable operational agility and better customer experience through real-time AI-driven streaming analytics allowing accurate alerts in seconds. It is designed to shorten MTTD and MTTR by providing real-time visibility into cloud infrastructure and services.
$180
per year per host
Pricing
Datadog
Dynatrace
Splunk Observability Cloud
Editions & Modules
Log Management
$1.27
per month (billed annually) per host
Infrastructure
$15.00
per month (billed annually) per host
Standard
$18
per month per host
Enterprise
$27
per month per host
DevSecOps Pro
$27
per month per host
APM
$31.00
per month (billed annually) per host
DevSecOps Enterprise
$41
per month per host
Synthetic Monitoring
$0.001
per synthetic request
Kubernetes Platform Monitoring
$0.002
per hour for any size pod
Real User Monitoring
$0.00225
per session
Application Security
$0.018
per hour for 8 GIB host
Infrastructure Monitoring
$0.04
per hour for any size host
Full-Stack Monitoring
$0.08
per hour for 8 GIB host
Infrastructure
$15
per month (billed annually) per host
App & Infra
$60
per month (billed annually) per host
End-to-End
$75
per month (billed annually) per host
Offerings
Pricing Offerings
Datadog
Dynatrace
Splunk Observability Cloud
Free Trial
Yes
No
Yes
Free/Freemium Version
Yes
No
No
Premium Consulting/Integration Services
No
No
No
Entry-level Setup Fee
Optional
No setup fee
No setup fee
Additional Details
Discount available for annual pricing. Multi-Year/Volume discounts available (500+ hosts/mo).
Easier to set up and integrate with other auxiliary tools. The cost was also a benefit along with self-service capabilities. We could set up Data Dog by ourselves, versus needing to bring additional consulting efforts to setup Dynatrace. Reliability of results (less false …
Dynatrace was cheaper but, in my opinion, its setup, features, and overall user experience do not come close to what Datadog can offer, making it more of a pain to use and not worth the cheaper cost over Datadog (especially if migrating away from Datadog to Dynatrace).
First think first - it's easy to use, and very easy to implement in any infrastructure. It provides a custom dashboard and monitors. I’ve used or evaluated Grafana, Prometheus, Amazon CloudWatch, and Dynatrace, and each tool has strong capabilities. Prometheus + Grafana provide …
Datadog is best for cloud-native and fast-setup. It is more mature for infrastructure and real-time observability. The UI is more user-friendly and provides wide coverage of app insights.
UI of the Datadog is easy to understand and integration steps are easy to understand. It also provides the troubleshooting steps which are easy to understand. Supports multi cloud integrations which is very important for all the customers to know about the cloud service's …
Verified User
Engineer
Chose Datadog
I selected Datadog because of its features and the wide range of integration support. As I already told it supports more that 600+ integrations which helps and organization to keep everything in a single place and also its AI feature which is reducing the time for root cause …
Datadog crushed the competition on price and offering more solutions in one product cutting down on implementation time and effort while ensuring that the "integration" between one of their offerings was completely compatible with any of the others. I'm sure it's not the case …
The first reason for selecting Datadog was of course it's pricing which is quite better in terms of competitor like AppDynamics and splunk. Second thing is versatile services which they are offering on one platform which means entire end to end services can be monitor at one …
It's a one-stop solution for all our needs whereas in other open-source tools, we have an operational overhead to keep and manage the uptime of these tools as well and also manage their versioning, upgrade, and patching cycle. Also if there are any bugs then we have to raise an …
Datadog is a little harder to use from an end user standpoint but is probably a little more flexible from a script/automation perspective; it has more granular permissions but default access is not ideal for our usage. Sensu doesn't do application performance monitoring. …
There are many pros and cons. For some use cases, Dynatrace far exceeds the capabilities of the competition--for instance in automatically detecting issues and performing root-cause analysis, Dynatrace is clearly ahead of the others. For cloud monitoring, Datadog seems to have …
Datadog is a good system but does lack a lot of features provided by Dynatrace, and more importantly, it does not have the support Dynatrace provides. Many other systems, Zabbix, Nagio, AppDynamics also exist, but so far, Dynatrace really shines above them all.
Dynatrace gives the overall picture of the application usage and performance by default with minimal configurations whereas in Datadog a lot of manual intervention is required to analyze the application performance and troubleshooting the issues. Dynatrace is user-friendly when …
Our technical team showed me the completeness of Dynatrace against the competitors. Also, the breadth of services Dynatrace offered was a selling point.
Dynatrace leads the pack when you are looking for application performance monitoring, but the other tools are better suited for certain areas of specialty. Elasticsearch is better than Dynatrace at log aggregation. Prometheus is better than Dynatrace at collecting custom …
Dynatrace is a premier tool for hybrid environments. It also happens to be the most expensive. Dynatrace is bad at pricing and customer success. They charge a premium but do offer one of the better solutions on the market.
Senior Director of Engineering Site Reliability, Performance & Capacity
Chose Dynatrace
Dynatrace provides the deep dive analysis on our pure paths like none other. The AI capabilities are very promising and helpful in our drive toward self-healing systems. We also like the bot, Davis, that can help solve some of the ops issues.
Splunk is superior in many ways to these solutions when I'm comes to ingesting, storing, manipulating, and using data, but dynatraces automatic agents do make it much easier to use out of the box. Nagios seems much cheaper but does not provide as much functionality as Splunk. …
I selected Splunk Observability Cloud because it focused so much on OTEL standards which will help us in future as OTEL is covering most of the observability standards. And also it has the best Kubernetes observability as I already explained it has several predefined dashboards …
The use of a single integration and definition of custom metrics, and tags is a great advantage. The ability to use SignalFlow to observe metrics in addition to the vast number of out-of-the-box dashboards is also excellent.
Splunk is better for Multicloud and UI is very good as compared to other Solutions. Also, time saving in case of Developer Productivity as Detectors can be saved as code.
SignalFX is a strong competitor in the monitoring SaaS space and provide the basic necessities for production grade monitoring and alerting. Other solutions may offer easier adoption and other helpful features, but will have trouble competing for cost for organizations that …
Datadog may be better suited for teams that have a more out-of-the-box infrastructure, on the primary platforms Datadog supports. You may also have better results if you have a bigger team dedicated to devops and/or a bigger budget. We found that trying to adapt it to our use case (small team, .NET on AWS Fargate) wasn't feasible. We continually ran into roadblocks that required us to dig through documentation (and at times, having to figure out some documentation was wrong), go back and forth with support, and in my opinion, waste money on excessive and unintended usages due to opaque pricing models and inaccurate usage reports, as well as broken/non-functional rate sampling controls.
Dynatrace is well suited to a number of tasks. It is important to determine who the end users are and gather good information to tailor their experience accordingly. For instance, business/marketing should not have access to some of the more technical data, and business metrics can be a distraction for IT operations personnel.
Its great if you need real-time visibility across complex or regulated environments. Also strong for hybrid or multi-cloud setups where uptime, observability and fast IR are required. It’s probably overkill for smaller teams or environments that don’t have constant changes or compliance reporting needs. It's expensive and has a steep learning curve. Also, in my opinion, do not get yourself into a consumption based model. Costs can certainly get out of control quickly.
The thing which Datadog does really well, one of them are its broad range of services integrations and features which makes it one step observability solution for all. We can monitor all types of our application, infrastructure, hosts, databases etc with Datadog.
Its custom dashboard feature which helps us to visualize the data in a better way . It supports different types of charts through those charts we can create our dashboard more attractive.
Its AI powered alerting capability though that we can easily identify the root cause and also it has a low noise alerting capability which means it correlated the similar type of issues.
We loved Dynatrace's ability to show the data flow - from the front end points through the back end points straight to the database and various API's. It was advanced in its data visualization. This is useful for debugging - showing when/where the errors are. It can even enable non-technical individuals in the corporation to help debug
Dynatrace has some great highly customizable integration options as well as monitoring. You can configure your layout & integration options to create custom monitoring alerts for your applications performance. Further you can increase the extensibility of using a REST API on your architecture.
Some advanced dev-ops systems are utilizing Kubernetes/docker aswell as Node.JS - Dynatrace was able to log and help understand all of our dev-ops needs. It gave us native alerts based off of deviations from the baseline that we set during initial configuration. These metrics are priceless.
The first one is its Kubernetes container monitoring.
I really like this features because as we know how much K8s is vast and to manually monitor each part of the Kubernetes it takes so much time but Splunk Observability Cloud makes it easier. And even once we integrate K8s with Splunk Observability Cloud it gives us some prebuilt dashboards which gives holistic view of our Cluster and its nodes, pods, etc.
The dashbaord feature of Splunk Observability Cloud, it gives us full flexibility to customize our dashboard with a wide range of predefined chart types.
Now it also supports OTEL, which is a plus point for observability. As now everyone is moving towards Otel and in current market there are only few tools who supports OTEL based integrations, Splunk Observability Cloud is one out of them.
Alert windows cause lag in notifications (e.g. if the alert window is X errors in 1 hour, we won't get alerted until the end of the 1 hour range)
I would appreciate more supportive examples for how to filter and view metrics in the explorer
I would like a more clear interface for metrics that are missing in a time frame, rather than only showing tags/etc. for metrics that were collected within the currently viewed time frame
Dynatrace does not monitor easily on a C-based application.
The way DPGR is addressed by Dynatrace is not very complete, and not clear. One thing is to mask the IP and request attributes but is not enough, the replay session feature is great but raises serious questions about user tracking.
You can use table-like functionality to generate dashboards, but these queries are heavy on the system.
It could be easier to give insight into what type of line parsing is used for specific documents in a company-managed environment and/or show ways to gain the insights needed.
I would like to see ways to anonymize specific data for shared reports without pre-formatting this in a dashboard on which reports could be based.
We have already renewed our purchase with the company. They make it easy for us to get a temporary license for our contingency site that is only used for testing twice a year. We are expanding our license with for this tool. We find it very useful and will renew it again.
Good: Stable system with low error rate Easy to use for simple use cases Bad: UI is not very clear for complex usage Mobile view (when logged in from phone) is bad No library for .net
There are so many features that it can be hard to figure out where you need to go for your own use case. For example, RUM monitoring us buried in a "Digital Experience" sidebar setting when this is one of our key use cases that I sometimes struggle to find in the application. It appears that ECS + Fargate monitoring was recently released which is great because we had to build a lambda reporting solution for ephemeral task monitoring. But this new feature was never on my radar until I starting clicking around the application.
Dynatrace is great to use once you understand how to use it correctly and get used to the layout of it. While I do not actively use it every day, whenever I do use it, I do have to get refamiliarized with it. However, once you have your dashboards setup correctly with the data that you want to see when you first login to Dynatrace, it's amazing.
When there is an issue, it’s a win if one can easily identify the root cause. To do the same, it should allow the user to dig deep with multiple data points and compare the data and identify the anomaly. In this use case, it’s good to drive from Splunk 011y.
The support team usually gets it right. We did have a rather complicate issue setting up monitoring on a domain controller. However, they are usually responsive and helpful over chat. The downside would be I don’t think they have any phone support. If that is important to you this might not be a good fit.
Given that Dynatrace has become an informal industry standard, the plethora of information available on forums is massive. Most problems or roadblocks you come across are most likely (almost certainly, in fact) already solved and solutions available on these forums. The tech support at Dynatrace is also quite good, with prompt and knowledgeable people at their end.
Our logs are very important, and Datadog manages them exceptionally well. We frequently use Datadog services for our investigations. Use case: Monitor your apps, infrastructure, APIs, and user experience.
Key features:
Logs, metrics, and APM (Application Performance Monitoring)
Real-time alerting and dashboards
Supports Kubernetes, AWS, GCP, and other integrations
RUM (Real User Monitoring) and Synthetics
✅ Best for backend, server, and distributed systems monitoring.
Synthetic Monitoring automatically does what other products do only through the use of other tools or through the development of user applications that still have a high cost of maintenance. The other products are not immediately usable and require many customizations. Through the use of configuration automatisms, you can be immediately operational and, in our case, we detected several imperfections in the applications.
Splunk Infrastructure Monitoring provides far superior options for anybody using a complex hybrid multi-cloud environment and allows both your SOC and NOC to work together on the same data while driving their own insights. We found other products are still in the old world view of servers and agents residing together within a single data centre, but modern apps are no longer like this.