ArcSight Logger and Datadog are competitors in the log management and analytics category. Datadog appears to have the upper hand due to its real-time monitoring capabilities and intuitive dashboards.
Features: ArcSight Logger provides scalable data collection, SmartConnectors for integration, and comprehensive querying capabilities. It is robust for enterprise environments due to its ability to manage large volumes of data. Datadog offers real-time cloud monitoring, seamless integration options, and user-friendly dashboard creation. Its customization capabilities for dashboards and real user monitoring enhance the analytics experience.
Room for Improvement: ArcSight Logger needs enhanced analytics, a more intuitive interface, and better support for emerging technologies. Complexity and outdated features also require modern enhancements. Datadog faces challenges with pricing complexity and high costs with scaling use. Documentation inconsistencies and the need for a more user-friendly interface are other areas for improvement.
Ease of Deployment and Customer Service: ArcSight Logger predominantly offers on-premises deployment, requiring on-site maintenance that can be challenging without adequate technical capacity. Support ratings vary, with some dissatisfaction reported post-acquisitions. Datadog provides versatile deployment options from private to hybrid cloud setups, supporting varied environments. Known for responsive customer service, Datadog also offers extensive documentation to facilitate cloud-centric scalability and onboarding.
Pricing and ROI: ArcSight Logger is noted for higher costs, reflecting enterprise-grade offerings and complexity, with investment justified for security and compliance benefits. Its pricing is high compared to competitors but aligns with enterprise functionalities. Datadog's usage-based pricing is criticized for unpredictability and scaling costs. Despite this, users acknowledge the value gained and efficiency improved, with ROI dependent on usage discipline and cost management strategies.
We provide pre-implementation, implementation, and post-implementation support.
Splunk does much more than SIEM, including log analysis, user behavior analysis, threat intelligence, and customer behavior analysis.
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.
There should be a clearer view of the expenses.
The setup cost for Datadog is more than $100.
ArcSight Logger installs on very minimal resources with very few requirements
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.
The technology itself is generally very useful.
Datadog is a comprehensive cloud monitoring platform designed to track performance, availability, and log aggregation for cloud resources like AWS, ECS, and Kubernetes. It offers robust tools for creating dashboards, observing user behavior, alerting, telemetry, security monitoring, and synthetic testing.
Datadog supports full observability across cloud providers and environments, enabling troubleshooting, error detection, and performance analysis to maintain system reliability. It offers detailed visualization of servers, integrates seamlessly with cloud providers like AWS, and provides powerful out-of-the-box dashboards and log analytics. Despite its strengths, users often note the need for better integration with other solutions and improved application-level insights. Common challenges include a complex pricing model, setup difficulties, and navigation issues. Users frequently mention the need for clearer documentation, faster loading times, enhanced error traceability, and better log management.
What are the key features of Datadog?
What benefits and ROI should users look for in reviews?
Datadog is implemented across different industries, from tech companies monitoring cloud applications to finance sectors ensuring transactional systems' performance. E-commerce platforms use Datadog to track and visualize user behavior and system health, while healthcare organizations utilize it for maintaining secure, compliant environments. Every implementation assists teams in customizing monitoring solutions specific to their industry's requirements.
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