

NETSCOUT nGeniusONE and Datadog compete in the network and application performance monitoring category. Datadog seems to have the upper hand due to its seamless integration capabilities and holistic view of performance metrics.
Features: NETSCOUT nGeniusONE includes advanced traffic analysis, packet inspection, and comprehensive network visibility. Datadog offers robust integration capabilities, real user monitoring, customizable dashboards, and application performance monitoring (APM).
Room for Improvement: NETSCOUT nGeniusONE could benefit from a more intuitive interface and less reliance on physical agents. Datadog faces criticism for its complex pricing model, dense UI, and integration flexibility improvements.
Ease of Deployment and Customer Service: NETSCOUT nGeniusONE is primarily used on-premises with direct technical support. Datadog is preferred for its cloud flexibility but relies more on documentation and user-driven exploration.
Pricing and ROI: NETSCOUT nGeniusONE is considered expensive, necessitating cost justification with its advanced features, while Datadog offers flexible plans with careful management required to prevent cost overruns with extensive logging.
Previously we had thirteen contractors doing the monitoring for us, which is now reduced to only five.
Datadog has delivered more than its value through reduced downtime, faster recovery, and infrastructure optimization.
I believe features that would provide a lot of time savings, just enabling you to really narrow down and filter the type of frustration or user interaction that you're looking for.
When I have additional questions, the ticket is updated with actual recommendations or suggestions pointing me in the correct direction.
Overall, the entire Datadog comprehensive experience of support, onboarding, getting everything in there, and having a good line of feedback has been exceptional.
I've had a couple instances where I reached out to Datadog's support team, and they have been really super helpful and very kind, even reaching back out after resolving my issues to check if everything's going well.
They need to work on their response time and overall competence.
The distributor's support is rated an eight out of ten, indicating room for improvement in SLA handling.
I am actually happy with technical support from NETSCOUT.
Datadog's scalability has been great as it has been able to grow with our needs.
We did, as a trial, engage the AWS integration, and immediately it found all of our AWS resources and presented them to us.
Datadog's scalability is strong; we've continued to significantly grow our software, and there are processes in place to ensure that as new servers, realms, and environments are introduced, we're able to include them all in Datadog without noticing any performance issues.
The solution is highly scalable and accommodates the growth needs effectively.
It is not similar to software solutions Datadog or Dynatrace where they can easily add agents without problems.
Datadog is very stable, as there hasn't been any downtime or issues since I've been here, and it's always on time.
Datadog seems stable in my experience without any downtime or reliability issues.
Datadog seems to be more stable, and I really want to have a complete demo before making a call to decide on this.
Datadog is more stable than NETSCOUT nGeniusONE, being a SaaS-based solution compared to on-prem solutions like NETSCOUT.
I rate the stability of NETSCOUT nGeniusONE as ten out of ten since we have not experienced any escalations or downtime issues from the end user's side.
Customers are more sensitive about NETSCOUT nGeniusONE's upgrades because it has hardware.
It would be great to see stronger AI-driven anomaly detection and predictive analytics to help identify potential issues before they impact performance.
We want to be able to customize the cost part, and we would appreciate more granular access control.
The documentation is adequate, but team members coming into a project could benefit from more guided, interactive tutorials, ideally leveraging real-world data.
Customers want to have service assurance, including NPM and APM, from one vendor.
It would be beneficial to see more AI capabilities included in nGeniusONE to further streamline processes.
Many big companies Samsung and Hyundai try to build their own monitoring solutions using open-source tools and their own engineers, though it has not been successful.
The setup cost for Datadog is more than $100.
Everybody wants the agent installed, but we only have so many dollars to spread across, so it's been difficult for me to prioritize who will benefit from Datadog at this time.
My experience with pricing, setup cost, and licensing is that it is really expensive.
The cost depends on the size of the customer, as sizing controls the pricing.
Regarding its high price, I give NETSCOUT nGeniusONE a seven.
Our architecture is written in several languages, and one area where Datadog particularly shines is in providing first-class support for a multitude of programming languages.
Having all that associated analytics helps me in troubleshooting by not having to bounce around to other tools, which saves me a lot of time.
Datadog was able to find the alerts and trigger to notify our team in a very prompt manner before it got worse, allowing us to promptly adjust and remediate the situation in time.
The capability of real-time traffic intelligence is also very useful because it allows for the comparison between real-time and historical packet levels.
Their analysis capability actually surpasses other APM solutions, which is why customers love it.
The real-time insights that NETSCOUT nGeniusONE provides are very helpful.
| Product | Market Share (%) |
|---|---|
| Datadog | 2.4% |
| NETSCOUT nGeniusONE | 1.2% |
| Other | 96.4% |

| Company Size | Count |
|---|---|
| Small Business | 80 |
| Midsize Enterprise | 46 |
| Large Enterprise | 99 |
| Company Size | Count |
|---|---|
| Small Business | 14 |
| Midsize Enterprise | 5 |
| Large Enterprise | 37 |
Datadog integrates extensive monitoring solutions with features like customizable dashboards and real-time alerting, supporting efficient system management. Its seamless integration capabilities with tools like AWS and Slack make it a critical part of cloud infrastructure monitoring.
Datadog offers centralized logging and monitoring, making troubleshooting fast and efficient. It facilitates performance tracking in cloud environments such as AWS and Azure, utilizing tools like EC2 and APM for service management. Custom metrics and alerts improve the ability to respond to issues swiftly, while real-time tools enhance system responsiveness. However, users express the need for improved query performance, a more intuitive UI, and increased integration capabilities. Concerns about the pricing model's complexity have led to calls for greater transparency and control, and additional advanced customization options are sought. Datadog's implementation requires attention to these aspects, with enhanced documentation and onboarding recommended to reduce the learning curve.
What are Datadog's Key Features?In industries like finance and technology, Datadog is implemented for its monitoring capabilities across cloud architectures. Its ability to aggregate logs and provide a unified view enhances reliability in environments demanding high performance. By leveraging real-time insights and integration with platforms like AWS and Azure, organizations in these sectors efficiently manage their cloud infrastructures, ensuring optimal performance and proactive issue resolution.
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