ScienceLogic and Datadog compete in the monitoring solutions category. Datadog appears to have the upper hand due to its feature-rich tools and robust real user monitoring capabilities, favored by users for distributed environment monitoring.
Features: ScienceLogic offers a customizable platform with multi-tenancy support, extensive event correlation, and AWS integration. Datadog provides versatile observability with broad integrations, application performance monitoring (APM), and synthetic testing, excelling in real user monitoring.
Room for Improvement: ScienceLogic's interface could be simplified, and its knowledge base needs enhancement. Users also note areas for improvement in SNMP trap processing and reporting capabilities. Datadog faces challenges with cost predictability and integration nuances, requiring more comprehensive documentation and pricing transparency.
Ease of Deployment and Customer Service: ScienceLogic offers flexible deployment for on-premises and hybrid cloud environments, making it suitable for complex infrastructures, while Datadog simplifies scaling across public and private clouds. ScienceLogic's customer service is praised for its responsive support, whereas Datadog users see room for improvement in pricing transparency despite its capable support.
Pricing and ROI: ScienceLogic operates on a device-based pricing model, offering clear ROI through incident reduction and improved monitoring capacity. Datadog is recognized for its feature richness but may be costly for smaller businesses, prompting users to monitor costs to prevent unexpected expenses.
The return on investment is fair but often challenged by medium-sized businesses who may question its adequacy.
I received excellent support from ScienceLogic.
Problems with Skylar may require longer wait times due to limited resource expertise.
We have a lab environment to test solutions before offering them to customers, ensuring everything works correctly.
The stability rating is nine out of ten, acknowledging some bugs, but indicating these are minor issues.
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.
The documentation is adequate, but team members coming into a project could benefit from more guided, interactive tutorials, ideally leveraging real-world data.
There should be a clearer view of the expenses.
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.
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.
The technology itself is generally very useful.
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.
It offers over 500 integrations with a wide range of device types, referred to as PowerPacks, which are prebuilt integrations for hundreds, if not thousands, of integration types.
The CMDB update and the automatic CMDB update are valuable.
Product | Market Share (%) |
---|---|
Datadog | 5.0% |
ScienceLogic | 1.7% |
Other | 93.3% |
Company Size | Count |
---|---|
Small Business | 78 |
Midsize Enterprise | 42 |
Large Enterprise | 82 |
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.
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