We performed a comparison between AWS X-Ray and Datadog based on real PeerSpot user reviews.
Find out what your peers are saying about Datadog, Dynatrace, New Relic and others in Application Performance Management (APM)."The VPN is one of the solution's most valuable features for us."
"It does everything we wanted it to do."
"Working with the solution is very easy. It's user-friendly."
"The simplicity of the dashboard is very good."
"We appreciate the way that this solution allows us to monitor the ongoing status of the UI at any given time."
"One valuable feature is that the synthetic alert stays open until the issue is resolved. You can actually monitor whether your system is back up."
"The monitoring so far has been good and we are happy with it."
"The breakdown of the response time of different components and getting in-depth details of the slow component are the most valuable features. It is easy to use, and it gets the job done."
"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."
"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 most valuable feature I have found is the elastic container service."
"Its logs are most valuable."
"The most valuable feature is the dashboards that are provided out of the box, as well as ones we were able to configure."
"It is great that creating an incident is possible from Slack while having all the relevant data in Datadog."
"We've been able to glean from the monitors what servers are down, and can alert the team in Slack."
"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."
"Datadog has made it much easier to have a central place for people to look for logs and made it much easier to notify them of any elevated error rates or failures."
"I haven't come across any features that are lacking."
"Documentation could be improved in New Relic APM, so users would have more clarity on configuring the dashboard. If New Relic gave better guidelines, users would find it easier to understand the metrics and features of New Relic APM. Another area for improvement is integration with Kubernetes. Currently, the process isn't user-friendly. It's challenging and lacks documentation for users to understand how to integrate New Relic APM with Kubernetes quickly. With multiple levels of Kubernetes dockers and other DBs on different clouds, it's tricky to gather all into New Relic APM on a single dashboard. What I'd like to see in the next version of New Relic APM is a single dashboard where you can easily view which applications fall under specific APMs. If there's a search feature where you can type in a keyword to find out if an APM is related to a particular application, that would be great."
"New Relic APM could improve error debugging and the correlation with the logs. We are receiving some alerts or alarms but we need to correlate with the error log, but it is difficult if it is more than seven months retention period, it is hard to trace. We need this especially for getting historical information."
"The older view is much better than the new view that they have. We'd like to go back to that previous version. The user interface just isn't as nice as it used to be."
"New Relic APM can improve the information when we dig deeper to check a problem. There should be more detailed information provided."
"I would like the ability to set up certain dummy accounts and do the actual things that the customer is doing, without impacting the production environment."
"It is very difficult to award the service level cycles at an endpoint level."
"How granular I could go down at looking at certain data, especially related to the operations, is limited."
"The user interface is sometimes kind of confusing to understand. It's not very user-friendly."
"Delta traces on the Golang profiler are extremely expensive concerning memory utilization."
"The pricing model could be simplified as it feels a bit outdated, especially when you look at the billing model of compute instances vs the containers instances."
"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 error traceability is an area that can be improved."
"I'm still exploring the trial version, and it is fine. One thing that I haven't been able to figure out is how to retrieve a report. This is something that could be improved. I probably need to navigate to a place to access the reports."
"The FinOps needs improvement."
"We need more advanced querying against logs."
"We need more visibility into the error tracking dashboard."
AWS X-Ray is ranked 30th in Application Performance Management (APM) with 1 review while Datadog is ranked 1st in Application Performance Management (APM) with 115 reviews. AWS X-Ray is rated 7.0, while Datadog is rated 8.6. The top reviewer of AWS X-Ray writes "Scalable and good for tracing problems, but hard to configure". On the other hand, the top reviewer of Datadog writes "Provides insightful analytics and good visibility that assist with making architectural decisions". AWS X-Ray is most compared with Azure Monitor, Google Stackdriver, Dynatrace, Elastic Observability and Splunk, whereas Datadog is most compared with Dynatrace, Azure Monitor, Amazon CloudWatch, Splunk and Google Stackdriver.
See our list of best Application Performance Management (APM) vendors.
We monitor all Application Performance Management (APM) 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.
