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.
"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."
"Using the data, our operation teams works with the dashboards to get their statistics, analytics, etc."
"We find they have a very helpful alert system."
"The many dozens of integrations that the solution brings out of the box are excellent."
"Anything I've wanted to do, I found a way to get it done through Datadog."
"We can handle debugging and find out why things are breaking in our applications."
"Datadog is constantly adding new features."
"With Datadog I can look at the health of the technology stack and services."
"Sentry is more accurate than some other tools such as Datadog because it has more integration with Slack, GitLab, Jira, or other ticketing tools."
"It's a great visibility tool for the developer team."
"The product performs well."
"Great for capturing application performance metrics and error logs."
"The most valuable feature we have found with Sentry is the security that it provides."
"Sentry is a pretty stable product... Sentry's documentation is pretty straightforward and neat."
"Its initial setup process is relatively straightforward."
"The most valuable feature is the ability to create and assign rules and give access to particular users."
"I often have issues with the UI in my browser."
"Datadog needs more local Asia-Pacific support, and if they don't have a SaaS solution in Asia-Pacific, they should offer an on-prem version. I'm told that's not possible."
"The Log Explorer could be better. I don't think it has log manipulation as Splunk does."
"Datadog is expensive."
"When the logs are too big, and Datadog splits them, the JSON format breaks and it is not so useful for us."
"The documentation leaves a lot to be desired for new users."
"While the tool is robust with many different capabilities, users would greatly benefit from more examples in the documentation."
"We need more integration functionality, including certain metrics integration."
"Lacks user metric tracking and the ability to create more dashboards."
"The settings for an administrator are complex."
"It should be easier to integrate Sentry with other tools, and the end-to-end tracing capabilities could be improved."
"Its debugging feature needs to be faster."
"I would like to see a role registration feature added."
"To deal with its shortcomings, Sentry needs to continuously improve in areas like the user interface and documentation, apart from its other features."
"The price could be lowered."
"I would like to have alert policies and alert conditions enhanced in the next release."
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.