

Find out in this report how the two AI Observability solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
It has reduced manual efforts that would otherwise be spent checking where spending is occurring and ensuring all teams use resources correctly.
I have seen a return on investment of 100%, with significant cost avoidance and measurable savings within the first few months of deployment.
I've seen a return on investment, as the savings are concrete, measurable, and they show up directly in the AWS bill.
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.
We have also seen fewer escalations for minor issues because alerts help us catch problems earlier, which indirectly reduces downtime and improves overall efficiency.
The additional support ended up taking longer than expected, with responses that did not meet our need for detailed and technical assistance.
Sometimes support needs to be reached, but they are very responsive and supportive.
The customer support for CloudCheckr is fantastic.
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.
If tomorrow I were to contract AWS or Google Cloud Services, I could manage them from the same place.
It scales well for MSPs and large enterprises, allowing for management of hundreds of accounts and tens of thousands of resources while retaining performance and visibility.
Datadog's scalability has been great as it has been able to grow with our needs.
Since it is a SaaS platform, we did not have to worry about backend scaling.
We have not faced any major performance issues from the platform side; it handles increased metrics and monitoring loads smoothly.
CloudCheckr is stable and rock solid.
Metrics collection and alerting have been consistent in day-to-day use.
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.
CloudCheckr is a powerful and feature-rich tool with abundant metrics.
Another area is drift analysis; there have been complaints about tracking optimization opportunities, such as how to track opportunities identified in January and whether they were resolved in February.
The data does not work in real time; rather, it takes between one and three days to show you the usage.
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.
Having more transparent and granular cost control features would make it easier to manage usage.
Overall, the pricing was quite convenient and represented good value for money.
Pricing is feature-tiered under the MSP licensing, and I would say the pricing was quite competitive and fair.
I won't pretend it's cheap, but we've saved multiples of what we pay for it, so the conversation with finance is straightforward.
The setup cost for Datadog is more than $100.
Pricing is mainly based on data ingestion, such as logs, metrics, and traces, and it can increase quickly if everything is enabled by default.
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.
The cost visibility and reporting are really valuable, and the dashboard is informative and enables good decision-making.
What makes CloudCheckr easy for me to use is its intuitive interface.
The best features CloudCheckr offers include out-of-the-box security and compliance check features that provide over 35 different types of compliance checks at no cost, best practice checks, and alerts.
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.
| Product | Mindshare (%) |
|---|---|
| Datadog | 4.2% |
| CloudCheckr | 0.6% |
| Other | 95.2% |


| Company Size | Count |
|---|---|
| Small Business | 5 |
| Midsize Enterprise | 1 |
| Large Enterprise | 10 |
| Company Size | Count |
|---|---|
| Small Business | 82 |
| Midsize Enterprise | 49 |
| Large Enterprise | 100 |
CloudCheckr offers a cohesive platform for managing cloud infrastructures with a focus on cost visibility, security, and compliance. Designed for multi-cloud environments, it provides insights and optimizations to enhance decision-making and resource efficiency.
CloudCheckr delivers thorough cloud management with features like cost analysis, security and compliance checks, and automated optimization suggestions. Its intuitive interface allows for easy deployment, supporting cost-saving measures. Users often find its cost visibility, multi-cloud integration capabilities, and granular reporting particularly beneficial. However, improvements can be made in areas such as Azure and Google Cloud integration, reporting capabilities, pricing model clarity, and UI complexity reduction.
What are CloudCheckr's key features?Industries using CloudCheckr benefit from enhanced cloud financial optimization and security monitoring. Managed service providers find it crucial for customer billing, while organizations leverage its multi-cloud support for maintaining compliance and governing usage. Specifically useful in sectors like finance and technology, it aids in data analysis and cost-saving strategies.
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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