

Datadog and ThousandEyes are leading competitors in the field of IT monitoring and analytics, with Datadog having an advantage due to its extensive integrations and cohesive data analysis capabilities.
Features: Datadog provides comprehensive monitoring capabilities without reliance on infrastructure, an intuitive user experience, and a wide range of integrations including AWS and Docker. ThousandEyes offers high scalability, effective end-user monitoring, and detailed analyses of internet and WAN performance, essential for cloud provider and ISP monitoring.
Room for Improvement: Datadog struggles with performance on large data sets, lacks some advanced application-level insights, and has complex pricing. Usability and integration options can be enhanced. ThousandEyes needs to expand its application monitoring capabilities and improve network device integration using protocols like SNMP. Its dashboards could also be more user-friendly.
Ease of Deployment and Customer Service: Datadog is flexible, supporting public, hybrid, and private cloud environments. Its customer service is generally reliable, though response times could improve. ThousandEyes focuses on on-premises and hybrid deployments and offers well-regarded support, but there's a demand for faster response times.
Pricing and ROI: Datadog's pricing is complex and usage-based, which can lead to unpredictable costs, but it shows strong ROI through operational efficiencies. ThousandEyes is seen as more cost-effective, usually based on flows rather than agents, benefiting those with Cisco agreements and providing significant ROI in Cisco-heavy environments.
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.
We contacted the support team, and they resolved it within a couple of hours.
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.
Scalability with ThousandEyes is straightforward as you don't really need to scale; it's designed to monitor multiple applications, accommodating 50 or 100 applications simultaneously.
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.
These incidents are related to log service, indexes, and metric capturing issues.
ThousandEyes is not very stable; sometimes you have to reboot the servers to get actual results.
It would be great to see stronger AI-driven anomaly detection and predictive analytics to help identify potential issues before they impact performance.
The documentation is adequate, but team members coming into a project could benefit from more guided, interactive tutorials, ideally leveraging real-world data.
In future updates, I would like to see AI features included in Datadog for monitoring AI spend and usage to make the product more versatile and appealing for the customer.
Having a dedicated incident alert system for URL alerts would help manage noise and streamline operations, especially during patch upgrades.
An area where ThousandEyes can be improved is in providing more in-depth packet analysis; we've found instances where ThousandEyes indicates everything is okay, but it's actually not.
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.
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.
I find the most valuable feature of ThousandEyes is the ability to directly see the client's exact issue.
The best features ThousandEyes offers include monitoring page load times, assessing how long it takes for an application to load, checking for packet loss and jitter, and monitoring the routing path from the user to the server hosted in the cloud or on-premises.
| Product | Market Share (%) |
|---|---|
| Datadog | 3.1% |
| ThousandEyes | 3.4% |
| Other | 93.5% |


| Company Size | Count |
|---|---|
| Small Business | 80 |
| Midsize Enterprise | 46 |
| Large Enterprise | 94 |
| Company Size | Count |
|---|---|
| Small Business | 5 |
| Midsize Enterprise | 2 |
| Large Enterprise | 11 |
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.
ThousandEyes is a Network Intelligence platform that delivers visibility into every network an organization relies on, whether public or private. ThousandEyes enables users to optimize application delivery, end-user experience and ongoing infrastructure investments.
With cloud, enterprises can innovate much faster, but the growing number of cloud and SaaS applications means that more apps are being delivered over the Internet. This increases dependence on the Internet, a public “best effort” network, and other third-party infrastructures, substantially reducing the ability of IT teams to predict, visualize and control operational behavior. This results in a chaotic and unmanageable IT environment, making issue resolution a time-consuming ordeal, potentially impacting reputation and revenue. ThousandEyes has innovated an approach based on an unmatched distribution of smart agents across the Internet and enterprise, providing visibility all the way to the end user. ThousandEyes gathers and analyzes massive volumes of Network Intelligence data from all of these vantage points, enabling organizations to solve even their most obscure performance problems in minutes. By using ThousandEyes in the planning and testing phases of cloud adoption, customers can also strategically identify and fix underlying problems before production deployment of business-critical applications.
The ThousandEyes solution is ubiquitous across industry sectors, and since launching in mid-2013, customers have come from a diverse set of industry sectors, which include Silicon Valley technology companies, financial services, healthcare, pharmaceuticals, retail, manufacturing and education.
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