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."
"The RUM solution has improved our ability to triage faster and hand more capabilities to our customer support."
"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've found it most useful for managing Rstudio Workbench, which has its own logs that would not be picked up via Cloudwatch."
"It has a high-level insight into the infrastructure model of the application and provides important detailed data on the host and metrics, which is the main concern of our customers."
"Datadog has clear dashboards and good documentation."
"The solution is sufficiently stable."
"Its logs are most valuable."
"It helps us better manage our logs."
"Provides agentless monitoring so there's no need to install the agent on each server."
"One of the valuable features is rapid dashboards."
"The tool is quite easy to deploy, and it offers very good support."
"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."
"Best feature of all is detailed monitoring of services, processes, ports and SSL certificates and or web content."
"The power flow is great."
"Dynamic Component Mapping is key and unique."
"It has good monitoring capabilities across cloud environments, data centers, and hybrid environments."
"The Wi-Fi side needs improvement."
"The technical support needs improvement."
"Deploying the agents is still very manual."
"The error traceability is an area that can be improved."
"They could have better log reporting."
"Datadog could be improved if it could detect other software in a container or server."
"It would be great if usage metrics were automatically created and we could create custom metrics, instead we ended up building some of our own stuff to track and alert on our own usage."
"I would like the tooling to have better integration in Slack, specifically sending out reminders to the relevant people to take breaks, do a retrospective, and specify with emojis which messages to log."
"I found the documentation can sometimes be confusing."
"The product could do better with its notifications."
"It was challenging onboarding users."
"One important area we feel could be improved is the UI. It takes a lot of clicks to do very simple tasks."
"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."
"Admins do not have direct access to the reporting."
"ScienceLogic could improve the implementation, it could be made easier."
"They should improve database issues in HA and Failover mode, and provide documentation for all users , even if they are not customers."
"They need a little more self-service."
"The product's reporting functionalities have certain shortcomings, making it an area where improvements are required."
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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.
See our list of best IT Infrastructure Monitoring vendors, best Network Monitoring Software vendors, and best Cloud Monitoring Software vendors.
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.