We performed a comparison between AWS X-Ray and Datadog based on our users’ reviews in five categories. After reading all of the collected data, you can find our conclusion below.
Features: AWS X-Ray excels in error identification and resolution, providing comprehensive information for debugging capabilities. It also offers compliance and security features, as well as performance insights and event flow analysis. Datadog is known for its user-friendliness for development teams, offering dashboards, error reporting, and ease of use. It also provides logs and analysis, troubleshooting and instrumentation capabilities, and infrastructure monitoring. Datadog also offers APM and tracing capabilities, as well as observability features. While AWS X-Ray focuses on error identification and resolution, compliance, security, and performance insights, Datadog emphasizes user-friendliness, flexibility, and a wide range of integrations and additional features. AWS X-Ray could benefit from better log filtering, an improved user interface, better data interpretation, and potentially allocating more resources. Datadog could focus on improving usability, reducing the learning curve, monitoring external websites, ensuring SSL security, and addressing additional areas for improvement.
Service and Support: AWS X-Ray's customer service has minimal feedback, indicating that customers rarely need assistance. Datadog's customer service has received a mix of opinions. Some users appreciate the quick and supportive help, while others have encountered delays or unhelpful responses.
Ease of Deployment: Setting up AWS X-Ray is moderately challenging, involving the need for research and documentation. This process typically takes around one to two days to complete. The initial setup for Datadog is generally regarded as simple and direct, with the time required ranging from one hour to three days, depending on the complexity of the setup.
Pricing: AWS X-Ray is seen as a cost-effective option for setup, particularly for companies looking to scale up. Users have mixed experiences with Datadog's pricing and licensing, with some finding it costly and perplexing.
ROI: AWS X-Ray does not provide clear details about its ROI. That said, many users have reported experiencing substantial returns from using it. Datadog's ROI differs among users, with some expressing positive sentiments and estimating an ROI ranging from 10x to 20x.
Comparison Results: AWS X-Ray is preferred over Datadog. AWS X-Ray excels in identifying and resolving errors, providing a centralized location to view related requests and efficient issue detection. It also offers comprehensive information such as IP addresses and user locations, ensuring compliance and security.
"AWS X-RAY identifies bottlenecks in terms of stability and performance and how long certain data lives in terms of response time and duration."
"The most important one is compliance. We're able to achieve our regulatory levels. We're able to achieve the security level that we need for the federal government."
"AWS X-Ray is a strong solution and has a smooth integration process."
"The solution has made it easier for us to trace the problems that we have with our requests and to monitor the timing of each step in each request we do in our endpoints."
"The most promising feature of AWS X-Ray is that you can debug the issues through the proper logs. You can also get an analysis out of the logs for some use cases, though I have yet to try all the features of AWS X-Ray."
"It is a very scalable solution."
"It has empowered all our platform engineers with a very powerful and easy to use monitoring system."
"Most of the features in the way Datadog does monitoring are commendable and that is the reason we choose it. We did some comparisons before picking Datadog. Datadog was recommended based on the features provided."
"The full stack of integrations made it easier to monitor the different technologies and platform providers, including Software as a Service providers, that otherwise would need a lot of work and customization to be able to see what is happening."
"We enjoy the multistep API tests."
"They have a very good foundation in capturing metrics, logs, and traces. It's a very nice tool for that and it allows you to apply these monitoring tools in almost any technology."
"Sometimes it's more user friendly for development teams. There are some parts of Datadog that are more understandable for development teams. For example, the APM in Datadog works more manually and works like the tools in New Relic or Grafana, or Elastic. It is easier to understand for software development teams."
"It has saved us a lot of trouble in implementation."
"We've found it most useful for managing Rstudio Workbench, which has its own logs that would not be picked up via Cloudwatch."
"If you have a small team, it's probably overkill."
"I do not have any notes in terms of improvements."
"What needs to be better in AWS X-Ray is the log filtering. Predefined filters could be helpful because the power of analytics comes from how you can filter the data. I also want to see more KPIs from AWS X-Ray."
"They can improve how traces are sent to other providers."
"The user interface is sometimes kind of confusing to understand. It's not very user-friendly."
"Like most Amazon products, the user interface, configuration, and tuning aren't the easiest. That's the biggest reason why people tend to go to products like TerraForm and Terragrunt. We use TerraForm and Terragrunt. So, for setting things up and interacting with X-Ray, it's definitely the user interface that can be better."
"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 want to reduce having to go to different screens to obtain all the information."
"While I like the ease of use, when compared with Tenable Nessus they could still improve their usability."
"Datadog lacks a deeper application-level insight. Their competitors had eclipsed them in offering ET functionality that was important to us. That's why we stopped using it and switched to New Relic. Datadog's price is also high."
"The real issue with this product is cost control."
"Ingesting data from various sources to monitor the log metrics of the system can always improve so that, if something goes wrong, the right teams are alerted."
"I found the solution to be stable, I did not experience any bugs or glitches. However, some of the managing team did."
"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."
AWS X-Ray is ranked 14th in Application Performance Monitoring (APM) and Observability with 6 reviews while Datadog is ranked 1st in Application Performance Monitoring (APM) and Observability with 137 reviews. AWS X-Ray is rated 8.0, while Datadog is rated 8.6. The top reviewer of AWS X-Ray writes "Saves time, is relatively cheap, and helps find errors". On the other hand, the top reviewer of Datadog writes "Very good RUM, synthetics, and infrastructure host maps". AWS X-Ray is most compared with Azure Monitor, New Relic, Sentry, Google Cloud's operations suite (formerly Stackdriver) and Grafana, whereas Datadog is most compared with Dynatrace, Azure Monitor, New Relic, Elastic Observability and AppDynamics. See our AWS X-Ray vs. Datadog report.
See our list of best Application Performance Monitoring (APM) and Observability vendors.
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