

ScienceLogic and Datadog are both key players in the infrastructure monitoring market, each bringing unique strengths to the table. ScienceLogic is seen as more customizable, offering granular monitoring, while Datadog is appreciated for its user-friendliness and extensive integrations.
Features: ScienceLogic provides a customizable monitoring platform featuring dynamic apps and high integration flexibility, which makes it effective for infrastructure monitoring. Its multi-tenant environment and event management are beneficial for serving multiple clients. Datadog excels in seamless integrations and robust APM and log management, with users favoring its ease of use and comprehensive visibility across platforms.
Room for Improvement: ScienceLogic users mention the complexity of its interface and reporting capabilities, seeking better API integration and improved event automation. Datadog users highlight billing model complexity and the need for improved API consistency, intuitive UI elements, and enhanced cost control.
Ease of Deployment and Customer Service: ScienceLogic is mainly deployed on-premises and receives high marks for its customer support, aiding deployment and operations. Datadog, used in public and hybrid cloud environments, also garners praise for customer service despite a learning curve, with a support team that effectively manages cloud implementations.
Pricing and ROI: ScienceLogic's pricing is fair but can be expensive for large deployments, with positive ROI through improved incident management for larger enterprises. Datadog's usage-based pricing offers flexibility but can rise quickly with usage; the cost is justified by the insights provided, although it poses challenges for smaller organizations.
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.
The return on investment is fair but often challenged by medium-sized businesses who may question its adequacy.
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.
Problems with Skylar may require longer wait times due to limited resource expertise.
I received excellent support from ScienceLogic.
We have a lab environment to test solutions before offering them to customers, ensuring everything works correctly.
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.
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.
Stability should relate to whether the platform fails, stops working, or breaks.
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.
While some other companies have easier APIs, using this solution demands significant expertise.
If the knowledge for implementation could be spread through articles, it would reduce this dependency.
Integrating observability and APM monitoring into the overall portfolio would be beneficial.
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.
It could be cheaper.
ScienceLogic is not that expensive and is cost-effective overall.
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.
Notably, its automation features, such as Runbook action, enable domain experts like me to execute one-click automation solutions, which contributes significantly to reducing MTTR.
The solution excels in three areas: application monitoring, server monitoring, and network performance monitoring.
The CMDB update and the automatic CMDB update are valuable.
| Product | Market Share (%) |
|---|---|
| Datadog | 4.8% |
| ScienceLogic | 1.7% |
| Other | 93.5% |


| Company Size | Count |
|---|---|
| Small Business | 80 |
| Midsize Enterprise | 46 |
| Large Enterprise | 95 |
| Company Size | Count |
|---|---|
| Small Business | 13 |
| Midsize Enterprise | 11 |
| Large Enterprise | 24 |
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.
ScienceLogic excels in customizable dashboards, seamless integrations, and real-time data analysis, supporting diverse IT environments with multi-tenant capabilities.
ScienceLogic provides robust infrastructure and network monitoring, catering to cloud, applications, and server environments. It supports hybrid setups, integrating with CMDB and ticketing systems while automating incident management. ScienceLogic's PowerPacks eliminate visibility gaps and its adaptable nature supports modern and legacy systems. Offering agentless monitoring, it ensures efficient operations with scalable infrastructure support and detailed reporting. However, the interface complexity and need for professional support can present usability challenges. Enhancements in reporting, application coverage, API support, and customization are desirable for improved user experience.
What are ScienceLogic's most important features?ScienceLogic is often implemented across industries requiring detailed attention to infrastructure and network monitoring. It finds utility in managing hybrid environments, integrating seamlessly with essential systems like CMDB and ticketing platforms. Its scalability and adaptability are valued in unifying complex, diverse environments under one monitoring platform.
We monitor all IT Infrastructure Monitoring 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.