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
Pricing
Datadog
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
Offerings
Pricing Offerings
Datadog
Free Trial
Yes
Free/Freemium Version
Yes
Premium Consulting/Integration Services
No
Entry-level Setup Fee
Optional
Additional Details
Discount available for annual pricing. Multi-Year/Volume discounts available (500+ hosts/mo).
I use Datadog because it concentrates all these features into a single tool, facilitating the learning curve that my platform and development engineering team needs in order to be able to set up the monitors/alerts/SLIs/SLOs as well as to diagnose a production issue. Its easier …
Datadog seems to be the most feature-rich of all the alternatives we've considered, however due to problems outlined earlier, some of the others have benefits. OpenTel can give us a way to make our platforms compatible with a variety of vendors, and can be done without …
Datadog is a more complex but complete solution than any of the other Log Aggregation, monitoring, or general observabilty tools that we have trialed. I found it easier to setup following useful and up-to-date documentation provided directly by Datadog instead of scattered …
Kibana Datadog … because within our usecase we have all the events in Kibana but sampled traces in Datadog … but if we had all the traces it would have been much more useful
I think Datadog and Sentry serve different needs. I like Sentry to keep track of errors on our systems. And then I'll jump into Datadog to investigate those issues.
We have utilized a SIEM in the past, but it was a very manual process to set it up. Content packs make it very easy to set up and get alerting instantly. Datadog takes out a lot of headaches for our security team, since they no longer have to create custom alerts for every …
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.
All other tools dont have all the features which Datadog provides. Easy to use from UI where other may have complicated UI or no UI at all to create monitors. Consider like AWS Grafana, we have limitation to create monitors from UI. There is no recurring downtime for monitors. …
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 …
we primarily use Kubernetes, and Prometheus is great for collecting time series metrics, especially in Kubernetes. and Grafana is used for dashboards. As these are open source, we host them and manage them internally. We choose Datadog because of its logs, traces, and …
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 …
1. Grafana is good, but a lot of integration is required for it to work. .that not the case of Datadog 2. Faster to set up Datadog instead of Grafana 3. Alerting in Datadog feels much easier thanin Grafana.
I have tried and used a number of other tools similar to Datadog such as New Relic, Splunk, Prometheus, AWS cloudwatch and Dynatrace. New Relic and Splunk provide excellent monitoring and analytics, but Datadog’s consolidated dashboards and ease of setup combined with a wealth …
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.
ease of use and implementation, other than New Relic (which I think is terrible in every possible way), the other two support opentelemetry better, have more manageable costs and comparable basic services, but they do not have the breadt of services dd does.
We moved to Datadog from Microsoft's Application Insights. Application Insights did a fine job in allowing us to view our application data, but it lacked the holistic view of all our infrastructure and other platforms that could not use Application Insights. Being able to …
In terms of usability, I’ve found Datadog significantly more approachable and powerful compared to Elasticsearch, especially for day-to-day operational monitoring. Datadog offers a much more cohesive, user-friendly interface out of the box, with built-in support for metrics, …
Datadog is an all in one solution. It has everything in one place so you don't have to go from application to application and try to figure out what exactly happened. No more stitching database errors from one third party to backend errors in another to front end errors in …
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.
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.
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
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.
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.
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.