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."
"It is a very scalable solution."
"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."
"AWS X-Ray is a strong solution and has a smooth integration process."
"It brings in observability, monitoring, and alerting capabilities - all of which we need to operate at scale."
"The ease of correcting these dashboards and widgets when needed is amazing."
"The solution allows flexibility and heightened observability for presenting data, creating indicators, and setting service-level objectives."
"The solution has offered increased visibility via logging APM, metrics, RUM, etc."
"The visibility that it provides is valuable. It is helping in being proactive around incident management. It is helping us to be able to get more visibility into our customers' applications so that we can assist them at the application layer. We also provide them the infrastructure from an AWS standpoint. We are able to make sure that our customers are aware of certain critical things around the analytical piece of either the network or the application. We're able to call customers before they even know about the issue. From there, we can start putting together some change management processes and help them a bit."
"Datadog documentation on web pages has improved a lot and is pretty easy to follow and find."
"Datadog is easy to use and easy to deploy. It's a better solution compared to others on the market in terms of being budget friendly for our customers."
"I don't have to worry about upgrades with the AWS version."
"They can improve how traces are sent to other providers."
"If you have a small team, it's probably overkill."
"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."
"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."
"The user interface is sometimes kind of confusing to understand. It's not very user-friendly."
"I do not have any notes in terms of improvements."
"Geo-data is also something very critical that we hope to see in the future."
"I find the training great. That said, it is set for the LCD (lowest common denominator). Of course, this is very helpful to sell the product, yet, to really utilize the product, you need to get more detailed."
"To be very fair, I haven't had enough experience with Datadog to pick out improvements."
"While the tool is robust with many different capabilities, users would greatly benefit from more examples in the documentation."
"I sometimes log in and see items changed, either in the UI or a feature enabled. To see it for the first time without proper communication can sometimes come as a shock."
"It would be nice to be able to graph metrics by excluding certain tags (like you can do in monitors)."
"When it comes to storing the logs with Datadog, I'm not sure why it costs so much to store gigabytes or terabytes of information when it's a fraction of the cost to do so myself."
"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."
AWS X-Ray is ranked 13th in Application Performance Monitoring (APM) and Observability with 6 reviews while Datadog is ranked 1st in Application Performance Monitoring (APM) and Observability with 136 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 Dynatrace, whereas Datadog is most compared with Dynatrace, Azure Monitor, New Relic, AppDynamics and Elastic Observability. See our AWS X-Ray vs. Datadog report.
See our list of best Application Performance Monitoring (APM) and Observability vendors.
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