We performed a comparison between Datadog and Prometheus based on our users’ reviews in five categories. After reading all of the collected data, you can find our conclusion below.
Features: Datadog offers a range of valuable features such as dashboards, error reporting, log centralization, and user-friendliness. It also provides troubleshooting and instrumentation capabilities, as well as flexibility and additional features. The interface and integrations are praised, along with its performance and infrastructure monitoring capabilities. Prometheus is highly regarded for its extensive range of APIs and libraries, flexibility in integration, and reliability as a monitoring solution. Its valuable dashboard, scalability, and fast data storage system are also commendable. Users appreciate the numerous integrations and the flexibility to tailor monitoring applications.
Users have pointed out several areas where Datadog can improve, including usability, integration, user interfaces, learning curve, organizational structure management, and customization flexibility. Prometheus users have suggested improvements in the query language, setup process, DSL and analysis tools, UI color and interface, stability, and documentation.
Service and Support: Users highly appreciate the customer service of Datadog for its quick response time and always being available to assist them. They receive immediate answers and timely support. Prometheus relies more on its documentation and online community for support, resulting in less frequent interactions with customer service.
Ease of Deployment: Users generally find the initial setup of Datadog to be simple and uncomplicated, often receiving help from service providers or technical support. Setting up Prometheus can be more complex. While some users find it easy, others note a learning curve and the necessity of online resources.
Pricing: Users find the setup cost of Datadog to be relatively high, and they recommend exploring cheaper alternatives or a free trial option. Prometheus does not require any payment for setup or licensing, making it a cost-effective choice compared to Datadog and similar options.
ROI: Some users of Datadog have mentioned time savings and fast debugging as positive results. Prometheus users have also experienced positive outcomes and ROI from their monitoring activities.
Comparison Results: Users prefer Prometheus over Datadog due to its cost-effectiveness, variety of APIs and libraries for easy integration, and flexibility. They also appreciate Prometheus's user-friendly setup, valuable features like the dashboard and metric collection, and the availability of an active online community for support.
"We really like the charts and visualization."
"We have been able to set very specific CPU and memory alerts, at the very base level, then we started to pull real business value, like 99th percentile response rates for our API calls."
"Datadog has so far been a breeze to use and set up."
"Datadog helps us detect issues early on and helps in troubleshooting."
"Even if we don't end up using Datadog, it revealed problems and optimizations to us that weren't obvious before."
"We've found it most useful for managing Rstudio Workbench, which has its own logs that would not be picked up via Cloudwatch."
"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 many dozens of integrations that the solution brings out of the box are excellent."
"It has lots of APIs and libraries to integrate with any kind of language."
"The good thing is it integrates well with the Grafana dashboard. It comes with a UI where you see everything as a graph."
"The product’s scalability is valuable."
"The most valuable feature is that we can receive information in different formats."
"It is an efficient solution."
"The feature I found most valuable is the number of integrations. It is the industry standard for metrics."
"Stability-wise, I rate the solution a ten out of ten."
"The solution is useful to collect huge metrics."
"This service could be less costly."
"We need to learn more about the session reply feature inside of DD."
"We need more integration functionality, including certain metrics integration."
"Lacks some flexibility in the customization."
"Could be a little more user friendly."
"Datadog isn't as mature as some of the established players like Dynatrace or Splunk. It's a new product, so they are constantly releasing new features, and I don't have much to complain about."
"I've found that the documentation is lacking in certain regards."
"We need more visibility into the error tracking dashboard."
"Setting up the rules in Prometheus can be confusing, making it an area where improvements are required."
"The simplicity of the query language could be improved. The current query language is not easy to work with."
"If you are not quite technical, it can be pretty hard to understand the way it works and how to query data in Prometheus."
"The setup could be made easier for new users because it requires a bit of advance knowledge or experience."
"When it comes to deployment, if you have no experience with something like a CI/CD pipeline, it might be a challenge."
"The scalability must be improved."
"Lacks the ability to clusterize."
"The product must improve its documentation."
Datadog is ranked 1st in Application Performance Monitoring (APM) and Observability with 137 reviews while Prometheus is ranked 9th in Application Performance Monitoring (APM) and Observability with 32 reviews. Datadog is rated 8.6, while Prometheus is rated 8.4. The top reviewer of Datadog writes "Very good RUM, synthetics, and infrastructure host maps". On the other hand, the top reviewer of Prometheus writes "A very flexible open box that can be used vastly to do anything you need". Datadog is most compared with Dynatrace, Azure Monitor, New Relic, AWS X-Ray and Elastic Observability, whereas Prometheus is most compared with Azure Monitor, New Relic, Dynatrace, Sentry and AWS X-Ray. See our Datadog vs. Prometheus 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.