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.
"This spectrum of solutions has allowed us to track down bugs faster and more rapidly, which allows us to limit revenue lost during downtime."
"The platform appeals to companies spanning many industries on a global scale."
"We rely heavily on the API crawlers that Datadog uses for cloud integrations. These allow us to pick up and leverage the tags teams have already deployed without having also to make them add them at the agent level."
"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."
"It has saved us a lot of trouble in implementation."
"The infrastructure monitoring capabilities are really valuable. You can just log on and see everything that is happening within an IT environment."
"The ease with which we can filter, use metrics, and give accounts to customers, then let the customer filter, set up metrics, and alerts. This has been a big win for us."
"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."
"The stability is very good for Sentry and in general works well."
"Sentry is a pretty stable product... Sentry's documentation is pretty straightforward and neat."
"The product performs well."
"The solution is user-friendly."
"The most valuable feature is the ability to create and assign rules and give access to particular users."
"Sentry breaks everything down in real time."
"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 documentation leaves a lot to be desired for new users."
"We would like to see some versioning system for the Synthetic Tests so that we could have a backup of our tests since they are time-consuming to make and very easy to damage in a moment of error."
"Even though it is powerful on its own, the UI-based design lacks elegance, efficiency, and complexity."
"It is very difficult to make the solutions fit perfectly for large organizations, especially in terms of high cardinality objects and multi-tenancy, where the data needs to be rolled up to a summarized level while maintaining its individual data granularity and identifiers."
"The Log Explorer could be better. I don't think it has log manipulation as Splunk does."
"I'm not sure if Datadog can monitor K8s deployments in real-time. For instance, being able to see a deployment step by step visually. This would be helpful if there were any incidents during the deployment."
"Once agents are connected to the Datadog portal, we should be able to upgrade them quickly."
"Datadog is so feature-rich that it is often hard to onboard new folks and tough to decide where to invest time."
"The log centralization and analysis could be improved in Sentry."
"I would like to have alert policies and alert conditions enhanced in the next release."
"It should be easier to integrate Sentry with other tools, and the end-to-end tracing capabilities could be improved."
"To deal with its shortcomings, Sentry needs to continuously improve in areas like the user interface and documentation, apart from its other features."
"I would like to see a role registration feature added."
"We cannot restrict particular columns on particular data. It would be helpful if that feature was improved."
"It would be nice if the product provided a map showing the users’ geographic location."
"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 AWS X-Ray. 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.
