We performed a comparison between Datadog and NETSCOUT vSTREAM based on real PeerSpot user reviews.
Find out in this report how the two Network Monitoring Software solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."The single dashboard is a valuable feature."
"We can manage the entire system across the network and troubleshoot the pain points."
"Profiling has been made easier."
"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."
"The solution has improved the organization by providing good insights into app performance and offering good dashboards."
"The service catalog helped improve our organization by giving a good view of the flow for our microservices applications."
"It lets us react more quickly to things going wrong. Whereas before, it might have been 30 minutes to an hour before we noticed something going on, we will know within a minute or two if something is off, which will let us essentially get something back up and running faster for our customers, which is revenue."
"I like the amount of tooling and the number of solutions they sold with their monitoring. Datadog was highly intuitive to use."
"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."
"Datadog dashboards are pretty great."
"One of the valuable features is the packet decoding."
"vSTREAM gives us better visibility and reporting about our network infrastructure, allowing for cost-optimization."
"The technical support needs improvement."
"The Wi-Fi side needs improvement."
"While I like the ease of use, when compared with Tenable Nessus they could still improve their usability."
"There are things about it that we would like to be fixed, such as it is taking averages of average. This results in data that we don't expect."
"One thing we have run into is that it is so easy to add monitoring that we turn on things without really understanding the costs."
"The ability to find what you are looking for when starting out could be improved."
"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 seems that admin cost control granularity is an afterthought."
"At times, it can be hard to generate metrics out of logs."
"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."
"I would like for it to have a smaller footprint of the virtual appliance and better performance."
"I would like to see improvements made to the user guide."
"Room for improvement exists in filtering in the packet decode."
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Datadog is ranked 2nd in Network Monitoring Software with 137 reviews while NETSCOUT vSTREAM is ranked 73rd in Network Monitoring Software. Datadog is rated 8.6, while NETSCOUT vSTREAM is rated 8.0. The top reviewer of Datadog writes "Very good RUM, synthetics, and infrastructure host maps". On the other hand, the top reviewer of NETSCOUT vSTREAM writes "Troubleshooting at the packet level helps us resolve issues more quickly". Datadog is most compared with Dynatrace, Azure Monitor, New Relic, AWS X-Ray and Elastic Observability, whereas NETSCOUT vSTREAM is most compared with vRealize Network Insight, Azure Network Watcher, Arista Data ANalyZer, NETSCOUT InfiniStreamNG and Ixia Network Taps. See our Datadog vs. NETSCOUT vSTREAM report.
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We monitor all Network Monitoring Software 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.