We performed a comparison between Datadog and Sentry based on our users’ reviews in five categories. After reading all of the collected data, you can find our conclusion below.
Features: Datadog offers useful features like dashboards, reporting, error reporting, log centralization, ease of use and setup, logs, and analysis, while Sentry excels in accuracy, integration with tools, error management, user-friendliness, and providing a rich context for error logs. Datadog requires improvements in usability, integration, SSL security, customization flexibility, documentation, and local support. Sentry could enhance issue automation, tracking capabilities, integration, pricing, and visual UX for administrators.
Service and Support: Datadog's customer service is highly praised for its availability and promptness, earning positive reviews. Sentry's customer service has limited feedback, but customers appreciate the helpfulness of the community support and documentation.
Ease of Deployment: Users generally find the initial setup for Datadog to be simple and uncomplicated, with some receiving help from service providers or technical support. However, a few users did find it complicated and needed to make further adjustments. Setting up Sentry initially is also easy and straightforward, offering various options. However, smaller companies may take up to three months for onboarding, and configuring a self-hosted server can be more difficult.
Pricing: The cost of setting up Datadog is subjective, with differing opinions among users. Some find it costly, while others find it reasonable. Users recommend trying the free plan before opting for a paid subscription. The pricing structure, particularly for log analytics and traffic-based expenses, can be perplexing. Sentry provides a free plan for initial projects and has affordable pricing for the paid version. Although some users find the license expensive, they believe it is worthwhile.
ROI: Users have reported different levels of ROI when using Datadog, with some highlighting the time saved and improved visibility into potential issues. Sentry has demonstrated favorable financial outcomes and advantages.
Comparison Results: Datadog is the preferred choice in comparison to Sentry. Users find Datadog easy to use and set up, appreciating its dashboards, reporting capabilities, error reporting, and log centralization. It is also praised for its user-friendliness for development teams and wide range of integrations. Datadog offers flexibility, observability, and additional features like AI and ML capabilities.
"We have found that we're able to get in and out of troubleshooting issues much more rapidly, which in turn, of course, enables us to spend more time on our products."
"The solution has offered increased visibility via logging APM, metrics, RUM, etc."
"The most valuable features are the dashboards and the reporting."
"It has empowered all our platform engineers with a very powerful and easy to use monitoring system."
"Since we integrated Datadog, we have had increased confidence in the quality of our service, and we had an easier time increasing our delivery velocity."
"The tool's deployment is easy."
"The initial setup is very straightforward."
"The integration and configuration are incredibly simple. The SaaS offering is remarkably easy to set up, especially if you're coming from a Graphite environment or anything that uses a StatsD."
"The most valuable feature we have found with Sentry is the security that it provides."
"Sentry breaks everything down in real time."
"The most valuable feature is the ability to create and assign rules and give access to particular users."
"Its initial setup process is relatively straightforward."
"It's a great visibility tool for the developer team."
"The product performs well."
"Sentry is more accurate than some other tools such as Datadog because it has more integration with Slack, GitLab, Jira, or other ticketing tools."
"The solution is user-friendly."
"At times, it can be hard to generate metrics out of logs."
"We need more visibility into the error tracking dashboard."
"I'm not sure what kind of features are in the roadmap right now, but I encourage the development of features for defining your organization, and allowing the visibility of what kind of metrics you can get. Those features would be really useful for us."
"We would like to see smaller or shorter tutorials and video sessions."
"The documentation leaves a lot to be desired for new users."
"It lacks consistency in the APIs."
"I would like testing for data in the future."
"They should continue expanding and integrating with more third-party apps."
"The price could be lowered."
"We cannot restrict particular columns on particular data. It would be helpful if that feature was improved."
"To deal with its shortcomings, Sentry needs to continuously improve in areas like the user interface and documentation, apart from its other features."
"The settings for an administrator are complex."
"The log centralization and analysis could be improved in Sentry."
"It would be nice if the product provided a map showing the users’ geographic location."
"Lacks user metric tracking and the ability to create more dashboards."
"Its debugging feature needs to be faster."
Datadog is ranked 1st in Application Performance Monitoring (APM) and Observability with 137 reviews while Sentry is ranked 8th in Application Performance Monitoring (APM) and Observability with 11 reviews. Datadog is rated 8.6, while Sentry is rated 8.6. The top reviewer of Datadog writes "Very good RUM, synthetics, and infrastructure host maps". On the other hand, the top reviewer of Sentry writes "An easy-to-use solution that has a good dashboard, performs well, and provides flexible pricing". Datadog is most compared with Dynatrace, Azure Monitor, New Relic, AWS X-Ray and Wazuh, whereas Sentry is most compared with Azure Monitor, Grafana, Elastic Observability, New Relic and Prometheus. See our Datadog vs. Sentry 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.