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.
$1.27
per month (billed annually) per host
Grafana Cloud
Score 8.5 out of 10
N/A
Grafana Cloud is a fully managed Observability Platform designed to aggregate, visualize, and analyze telemetry data across distributed architectures. The platform provides a unified environment for Metrics, Logs, Traces, and Continuous Profiling, utilizing the LGTM (Loki, Grafana, Tempo, Mimir) and Pyroscope stack to provide high-cardinality analysis of system state.
$8
per month up to 1 active user
Pricing
Datadog
Grafana 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
Grafana Cloud - Pro
$8
per month up to 1 active user
Grafana Cloud - Free
Free
10k metrics + 50GB logs + 50GB traces up to 3 active users
Grafana Cloud - Advanced
Volume Discounts
custom data usage custom active users
Grafana - Enterprise Stack
Custom Pricing
Offerings
Pricing Offerings
Datadog
Grafana Cloud
Free Trial
Yes
Yes
Free/Freemium Version
Yes
Yes
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
Optional
No setup fee
Additional Details
Discount available for annual pricing. Multi-Year/Volume discounts available (500+ hosts/mo).
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. …
Datadog is significantly more user-friendly than CloudWatch.In terms of capabilities, they're similar. I would not call either of the best-in-class for any single feature, but Datadog feels more polished and ready to use overall.Multi-cloud monitoring is a clear differentiator …
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 …
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.
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.
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, …
Grafana is more flexible, readily adopts other tools frameworks instead of forcing you to use their agent, doesn't force you into Vendor lock-in, and embraces open source, self-hosted, and Enterprise. Similar companies would like you to use their specific tooling and don't …
Grafana gives more flexibility to explore its features. A new user can explore experiment and work with free Grafana account and find if it is suitable for them.Other platforms don't have the features in their freemium version that Grafana has. It lets us try features of …
Grafana has a direct plugin to Icinga monitoring solution and allowed for easy configuration for us. At the time of implementation, other services did not have such an integration. As we already had a very customized and heavily introduced monitoring solution in place, we …
Grafana blows Nagios out of the water when it comes to customization. The ability to feed almost any data source makes it very versatile and the cost is great.
Datadog works really well with complex microservices architecture like any E-commerce platform which will be having multiple services but they all are interdependent to others so in this scenario Datadog will be best to monitor these as it will show the transactions also between those microservices. If you are using multiple services in your architecture whether it will be cloud services or on prem services Datadog will be the best choice to monitor all those service with in Datadog so that you can see everything in a single place. But if you are having small architecture and few services in that then in that scenario you can use Datadog but it will be little costly as compared to other but obviously the features are very well.
Just about any organization with more than one server and more than one cluster as it scales very well. Configuration of the application takes time and finesse to fine tune to where the balance of load time and getting data quickly meets. The plugins add load time but fine tuning for the application to meet demand needs nailed down at implementation
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 is some room for improvement, but the Datadog team sends out updates frequently, and the UI is user-friendly for engineers, with no significant loading issues or region-specific problems. That was one of the key reasons we preferred Datadog; our company has employees worldwide, and it wasn't difficult to transition to the tool.
Great usage in terms of monitoring of any application from backend to frontend and even any AWS resource via cloud watch and other connectors. Easy to use and configure personalised dash boarding and alerting features. Cost efficient and easy to setup and run, no mazor scaling challenges in terms of managing and maintaining the stack, easy to configure via Prometheus, influx and other connectors
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.
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 around many blogs or articles. I would love to have my own Grafana + Prometheus expert to setup all the peices we need but you're paying for expertise there instead of an experience with Datadog.
Grafana is more flexible, readily adopts other tools frameworks instead of forcing you to use their agent, doesn't force you into Vendor lock-in, and embraces open source, self-hosted, and Enterprise. Similar companies would like you to use their specific tooling and don't offer nearly as much flexibility. The other thing I like about Grafana is their storage usage is much lower compared to similar tools and competitors
