We compared Datadog and ScienceLogic across several parameters based on our users' reviews. After reading the collected data, you can find our conclusion below:
Features: Datadog users like its customizable displays, error tracking, and advanced AI/ML capabilities. ScienceLogic is highly regarded for its serverless and agent connectivity, versatile graphs and personalized dashboards, AIOps and event management capabilities, as well as its AI and machine learning features.
Room for Improvement: Datadog could enhance its usability and reduce its learning curve. Users said integration was another pain point. ScienceLogic can enhance its documentation, Power Packs, notification features, and automation options.
Service and Support: While many users spoke highly of Datadog’s support team, others reported slow support responses, especially in the Asia-Pacific region. ScienceLogic's customer service is generally considered responsive and professional. However, a few users reported delayed response times and support engineers with limited expertise.
Ease of Deployment: Datadog’s setup is considered straightforward, and users often receive help from a partner or vendor. ScienceLogic's initial setup is described as simple and efficient. The deployment process can be completed within a few hours or a couple of weeks.
Pricing: Opinions about Datadog's price are divided. Some users found it costly, but others thought it was acceptable. Some said the pricing model could be clearer and better explained. Opinions on the price of ScienceLogic were mixed. Pricing is determined by the number of network devices or endpoints, and there are no hidden charges.
ROI: Users said Datadog saved them time and improved visibility into security blind spots. ScienceLogic improves troubleshooting and minimizes network outages.
Comparison Results: Datadog is praised for its customizability, easy setup, and robust AI features, but some users say it has room for improvement in areas like usability and integration. Datadog’s pricing and customer service received mixed reviews. ScienceLogic is praised for its serverless and agent connectivity, effortless setup, and customized dashboards. However, it lacks detailed documentation and automation options.
"The single dashboard is a valuable feature."
"We can manage the entire system across the network and troubleshoot the pain points."
"Datadog dashboards are pretty great."
"It helps us better manage our logs."
"We have a better grasp of what is occurring during the deployment cycle. If something fails, we have an idea what has failed, where it has failed, and how it failed to better mitigate the situation."
"We have found that we're able to get in and out of troubleshooting issues much more rapidly, which in turn, of course, enables us to spend more time on our products."
"The initial setup is very straightforward."
"Since we integrated Datadog, we have had increased confidence in the quality of our service, and we had an easier time increasing our delivery velocity."
"Its integration is most valuable because you can integrate it with various service providers such as AWS, .Net, etc."
"I really enjoy the RUM monitoring features of Datadog. It allows us to monitor user behavior in a way we couldn't before."
"Dynamic Component Mapping is key and unique."
"ScienceLogic allows us to create and customize a user-friendly dashboard."
"The solution provides good infra-monitoring features."
"When it comes to features, the power pack is the most valuable."
"It is very easy to configure because we are using an agent-less version. You can very quickly implement a collector for monitoring device servers."
"The most valuable features of ScienceLogic are AI and machine learning."
"Its ITSM and EMS combination is really amazing. There is no need to purchase two products, one for ITSM and a second for EMS/NMS."
"One of the valuable features is rapid dashboards."
"The Wi-Fi side needs improvement."
"The technical support needs improvement."
"When the logs are too big, and Datadog splits them, the JSON format breaks and it is not so useful for us."
"It does not have the best interface."
"We have recently had a number of issues with stability and delays on logging, monitoring, metric evaluation, and alerts."
"When I started using it years ago, it had stability problems. I remember, specifically, we ran everything in Docker containers. There were some problems getting it into a Docker container with very specific memory limits."
"More granular control over dashboard sharing. Timeboard sharing."
"We would really like to see more from the Service Catalog."
"We need a lot of modules since we collect all data logs from all operating systems."
"We'd like Datadog to make the log storage cheaper."
"Addressing duplicate IPs: There is the ability to edit the DB and fix this, but adding some logic to understand them would be a plus."
"The product must educate its strategic partners for deployment."
"Admins do not have direct access to the reporting."
"ScienceLogic should provide detailed documents to customer as the current documents are not sufficient."
"They should improve their support process and add chat."
"The product's reporting functionalities have certain shortcomings, making it an area where improvements are required."
"It was challenging onboarding users."
"ScienceLogic could improve the implementation, it could be made easier."
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Datadog is ranked 2nd in IT Infrastructure Monitoring with 137 reviews while ScienceLogic is ranked 12th in IT Infrastructure Monitoring with 42 reviews. Datadog is rated 8.6, while ScienceLogic is rated 8.6. The top reviewer of Datadog writes "Very good RUM, synthetics, and infrastructure host maps". On the other hand, the top reviewer of ScienceLogic writes "Great integrations, power flow, and good support". Datadog is most compared with Dynatrace, Azure Monitor, New Relic, AWS X-Ray and Elastic Observability, whereas ScienceLogic is most compared with Dynatrace, LogicMonitor, SolarWinds NPM, Zabbix and ServiceNow Discovery. See our Datadog vs. ScienceLogic report.
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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.