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.
"We've found it most useful for managing Rstudio Workbench, which has its own logs that would not be picked up via Cloudwatch."
"The most valuable aspects of the product include the APM and profiler."
"It provides more cloud data. They tend to just get the way a service would be designed on the cloud."
"Datadog agents act as an integration to different services, providing easy access and management."
"Going from viewing a metric to creating a monitor alerting on a metric is very easy."
"Profiling has been made easier."
"The most valuable features have been: Sharable dashboards, TimeBoards, dogstatsd API, Slack Integration, Event logging API. CloudTrail Events, Tags, alerts, and anomaly detection. EBS Volume Snapshot Age, which they added upon request."
"Integrating Datadog with other platforms has made our monitoring processes a bit easier. It's not super simple, but it's manageable."
"The most valuable aspect is customization. There are many customizations possible, so I like that."
"It integrates well with other solutions."
"It excels in providing comprehensive details when there are downtimes or fluctuations, offering thorough reports."
"Collaboration: Shares data and dashboards across teams."
"The integration between Loki and Tempo is valuable."
"This solution provides valuable insights into the health of our infrastructure in real time."
"Compatibility with Prometheus databases and the Spring Boot application make it the first choice when moving toward an SRE model."
"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."
"The product could be improved by providing remote control to agents, enabling them to execute automation and collections without requiring another automation tool or integration."
"I would love to see more metrics or analytics in IoT devices."
"It seems that admin cost control granularity is an afterthought."
"Stability of the product has been a concern for us outside of the primary monitoring agents."
"I've only been using Datadog for a few months, and at first, it was frankly overwhelming in terms of both the UI and the available capabilities."
"I would like the tooling to have better integration in Slack, specifically sending out reminders to the relevant people to take breaks, do a retrospective, and specify with emojis which messages to log."
"Datadog does not have the feature where you can monitor external websites or check the SSL secure for websites."
"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."
"If there was an issue on one node, we couldn't drill down and see all the issues on other nodes."
"There are some areas of network drives that are not showing as expected based on server usage."
"The security needs to be improved, such as the capacity to add permissions on dashboards."
"It would be helpful if Grafana provided more information and training on how to use Prometheus."
"One area for improvement in Grafana is that depending on your version, you have to pay for the features, making the license expensive. It would be great if the licensing model could be more flexible. In the next release of Grafana, I want cluster creation to be available, which would help in Grafana deployment and scaling. Currently, the scaling process for the solution is a bit complicated."
"Setting up alerts via Grafana is a bit complicated, and alerting needs to improve."
"It is limited on the reporting type supported, which is important for managerial-level officers who want reports that are either general or specific."
"The solution should include online support."
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.