

Datadog and Graylog Enterprise are both competitive solutions in the IT and monitoring space. Datadog seems to have an edge with its comprehensive integrations and visualization capabilities across multiple cloud environments and systems like AWS, whereas Graylog Enterprise excels in its robust search and alerting features, particularly beneficial for security applications.
Features: Datadog offers an extensive range of integrations and easy-to-use dashboards, making it ideal for automated monitoring and analytics across various systems without the need for extensive infrastructure management. Key features include intuitive tagging and anomaly detection. Graylog Enterprise is distinguished by its superior alerting and search capabilities, providing detailed data management and the ability to quickly resolve issues and analyze logs efficiently due to its high-performance search engine.
Room for Improvement: Datadog could enhance its data analysis speed, custom metric tracking, and visual customization options. Users also seek more transparency in usage visibility and stability of certain features. Graylog Enterprise can improve its user interface and offer more flexible alert conditions. Better integration options and comprehensive documentation would enhance its user experience.
Ease of Deployment and Customer Service: Datadog is highly flexible, offering seamless deployment across public, private, and hybrid cloud environments. It generally receives favorable reviews for its responsive customer service, although some users desire more personalized support. Graylog, particularly robust on-premises or in private clouds, suits those experienced with manual implementations. While proactive support is available, real-time assistance access could be improved.
Pricing and ROI: Datadog's complex pricing model can lead to hidden costs, especially for scaling usage. However, its robust capabilities often justify the cost for larger organizations, offering value in operational efficiency despite the high initial expense. In contrast, Graylog's open-source option is cost-effective for smaller setups managing moderate data volumes. Its Enterprise version, although more expensive, provides a good ROI due to its effective log management and alerting features.
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.
Graylog allows our security team and IT engineers quick access to information, as it all goes to one place.
There have been financial savings as well and increased reliability, because I don't depend on a physical server hosted in my office.
Since I began using Graylog Enterprise, I perceive a return on investment, including a fifteen percent reduction in incident response time and twenty percent less time to find bugs.
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.
Customer support for Graylog Enterprise is excellent.
I would rate customer support a ten on a scale from one to ten because they were always very proactive with us, helping with whatever was required.
The support experience generally depends on the issue complexity, but the team was very responsive and their technical guidance was also very good and constant.
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.
More up-to-date documentation on how to do high ingestion and high search scenarios, including recommendations for configuration and deployment, would be useful.
I haven't needed to scale so far, but I believe it will meet my needs when I expand in the future.
The scalability of Graylog Enterprise is very good; it always responds to needs at the right time.
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.
Graylog Enterprise is completely stable.
I believe Graylog Enterprise is stable; it provides a lot of information about alerts, allowing good visibility of the client's environment.
Graylog Enterprise is stable.
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.
Mainly, it's about integrations: being able to parse different sources and output to different systems easier.
I understand that Graylog Enterprise is not a SIEM; it is a log management tool. However, it was able to meet my needs for security log monitoring specifically.
Writing the rules can be very tedious, especially since the documentation isn't extensive on how the functions provided for these rules work.
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.
It costs approximately $50,000 or $60,000 for 100 GB a day.
Regarding my experience with the price, configuration cost, and licensing of Graylog Enterprise, I consider that the cost-benefit ratio is very good when compared.
I worked in the SOC environment focusing more on analyzing alerts, but I was able to understand the configurations well, including setting up use cases and automations.
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 Graylog features that have proven to be most beneficial for our data analysis in particular are that we tend to use it as a big data store, so we have the correlation rules that, if something matches under certain conditions, it raises an alarm.
The best feature of Graylog Enterprise is its high-performance search engine that provides fast, flexible, and scalable analysis of machine data or pod data.
Monitoring improved by up to 80 percent because of having all the logs centralized.
| Product | Mindshare (%) |
|---|---|
| Datadog | 3.7% |
| Graylog Enterprise | 2.5% |
| Other | 93.8% |

| Company Size | Count |
|---|---|
| Small Business | 81 |
| Midsize Enterprise | 50 |
| Large Enterprise | 100 |
| Company Size | Count |
|---|---|
| Small Business | 13 |
| Midsize Enterprise | 6 |
| Large Enterprise | 13 |
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.
Graylog Enterprise, recognized for log collection, real-time search, and enriched data handling, offers an open-source framework that integrates seamlessly with Elasticsearch. Its user-centric interface streamlines data correlation and log aggregation, supporting both backend services and comprehensive monitoring needs.
Graylog Enterprise stands out for its stability and powerful log management capabilities, facilitating efficient log aggregation, real-time updates, and data analytics. Users benefit from its plugin-based alerting, user-friendly interface, and support for microservices, including Docker integration. The ability to search in detail, flexible API integration, and data enrichment features are highly valued. Challenges include collector application issues, desired visualization enhancements, and authentication integration improvements. Users seek advancements in UI customization, backup functions, and easier rule creation.
What are Graylog Enterprise's most important features?In industrial use, Graylog Enterprise is crucial for audit trailing in financial sectors, facilitating security event identification and error monitoring. Backend teams leverage real-time analytics for swift issue resolution, while developers appreciate the comprehensive log visualization enabled by Docker integration for microservice management.
We monitor all Log Management 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.