We performed a comparison between Datadog and Grafana based on our users’ reviews in five categories. After reading all of the collected data, you can find our conclusion below.
Features: Datadog offers impressive capabilities in dashboards, error reporting, ease of use, logs, and analysis, user-friendliness for development teams, and infrastructure monitoring. Grafana shines in creating visually appealing graphs, customization options, open-source nature, extensive visualization capabilities, import/export functionality, and capacity planning. Datadog has several areas for improvement including usability, integration, user interface intuitiveness, security features, organizational structure management, agent deployment, network monitoring, customization possibilities, and improved documentation for agent setup and debugging. Grafana could improve in data aggregation enhancement, expanding reporting types, logs integration for debugging, editing tool improvement, plugin capabilities expansion, and file-saving configuration improvement.
Service and Support: The opinions on Datadog's customer service are divided, as some users appreciate the quick and useful support, while others faced delays or unhelpful responses. Grafana's customer service has garnered positive feedback for being efficient and technically knowledgeable. Additionally, Grafana offers a valuable community forum for further assistance.
Ease of Deployment: Users generally find the initial setup for Datadog to be simple and uncomplicated, often with assistance from service providers or technical support. On the other hand, the initial setup for Grafana is mixed among users, as some find it easy while others report the need for resource optimization and tuning.
Pricing: Users express differing opinions on the pricing of Datadog, with some considering it expensive and others finding it reasonable compared to alternative solutions. Grafana provides a variety of choices, including a free open-source version, and offers moderately priced licensed options.
ROI: Users have different experiences with the ROI of Datadog, with some mentioned benefits such as time savings and reduced blind spots. On the other hand, Grafana is highly regarded for its data visualization and analytics capabilities.
Comparison Results: Grafana is the favored option when comparing it to Datadog. Users appreciate Grafana's customizable features, extensive visualization capabilities, and ability to create visually appealing graphs. The fact that Grafana is open source and cost-effective, with a supportive community, is also highly valued. Additionally, users find Grafana easy to use, with a friendly interface and helpful customer and technical support. Grafana's focus on data visualization and affordability makes it the preferred choice.
"Straightforward to integrate and automate."
"Datadog has clear dashboards and good documentation."
"I like the amount of tooling and the number of solutions they sold with their monitoring. Datadog was highly intuitive to use."
"Flame graphs are pretty useful for understanding how GraphQL resolves our federated queries when it comes to identifying slow points in our requests. In our microservice environment with 170 services."
"The ability to easily drill down into log queries quickly and efficiently has helped us to resolve several critical incidents."
"If we have a large load for users using our basic Datadog, it will immediately fire off an alert notifying us either something's wrong or not."
"The biggest thing I liked was the combination of all the things - monitoring, log aggregation, and profiling."
"It has a high-level insight into the infrastructure model of the application and provides important detailed data on the host and metrics, which is the main concern of our customers."
"It gives us the visibility we need. I like that when we add deployment markers or release markers, we know exactly when an issue arises. For instance, if there is an increased usage of CPU, we can link it directly to the deployment that might have caused the issue. It increases productivity and observability. We can now easily tell when a certain issue arises. It's way easier to debug because it can point you to certain things based on these markers, and we can debug easier."
"Kubernetes could help us to better visualize the trend of our data by recording and displaying our history over a chosen duration, such as the last 30 days."
"We like the alert features."
"The dashboards are very easy to work with."
"The integration between Loki and Tempo is valuable."
"The solution can scale well."
"It has good stability."
"The solution has good features."
"Datadog lacks a deeper application-level insight. Their competitors had eclipsed them in offering ET functionality that was important to us. That's why we stopped using it and switched to New Relic. Datadog's price is also high."
"The Log Explorer could be better. I don't think it has log manipulation as Splunk does."
"More granular control over dashboard sharing. Timeboard sharing."
"As a new customer, the Datadog user interface is a bit daunting."
"Once agents are connected to the Datadog portal, we should be able to upgrade them quickly."
"It would also be nice if we had more insight into our own usage of Datadog (agents and custom metrics). They provide a usage page which does help, but it is not in real-time."
"The product needs a better Datadog agent installation."
"Delta traces on the Golang profiler are extremely expensive concerning memory utilization."
"The technical support has room for improvement."
"There are not a lot of plugins for financial market monitoring."
"I would like the ability to download my results into any format in order to share the information with my clients."
"The service dashboard is very hard and needs improvement."
"It would be helpful if Grafana provided more information and training on how to use Prometheus."
"Multiple dashboards combined into one dashboard has slowed things down for us."
"Grafana doesn't provide anything for reporting."
"The documentation or training provided by Grafana is limited compared to its competitors, like Splunk."
Datadog is ranked 1st in Application Performance Monitoring (APM) and Observability with 137 reviews while Grafana is ranked 6th in Application Performance Monitoring (APM) and Observability with 39 reviews. Datadog is rated 8.6, while Grafana is rated 8.0. The top reviewer of Datadog writes "Very good RUM, synthetics, and infrastructure host maps". On the other hand, the top reviewer of Grafana writes "Agent-free with great dashboards and an active community". Datadog is most compared with Dynatrace, Azure Monitor, New Relic, AWS X-Ray and SCOM, whereas Grafana is most compared with New Relic, Azure Monitor, Sentry, Dynatrace and ITRS Geneos. See our Datadog vs. Grafana report.
See our list of best Application Performance Monitoring (APM) and Observability vendors.
We monitor all Application Performance Monitoring (APM) and Observability reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.