We performed a comparison between Datadog and Logz.io based on our users’ reviews in five categories. After reading all of the collected data, you can find our conclusion below.
Comparison Results: Datadog is the winner in this comparison. According to reviews, Datadog appears to be a more mature and powerful solution. Logz.io does come out on top in the setup and pricing categories, however.
"With Datadog I can look at the health of the technology stack and services."
"I have found the logging and tracing features the most valuable."
"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."
"Having a clear view, not only of our infrastructure but our apps and services as well, has brought a great added value to our customers."
"The tools are powerful and intuitive to set up."
"Datadog is easy to use and easy to deploy. It's a better solution compared to others on the market in terms of being budget friendly for our customers."
"Datadog is providing efficiency in the products we develop for the wireless device engineering department."
"It provides more cloud data. They tend to just get the way a service would be designed on the cloud."
"The visualizations in Kibana are the most valuable feature. It's much more convenient to have a visualization of logs. We can see status really clearly and very fast, with just a couple of clicks."
"We use the tool to track the dev and production environment."
"We use the product for log collection and monitoring."
"The tool is simple to setup where it is just plug and play. The tool is reliable and we never had any performance issues."
"It is massively useful and great for testing. We can just go, find logs, and attach them easily. It has a very quick lookup. Whereas, before we would have to go, dig around, and find the server that the logs were connected to, then go to the server, download the log, and attach it. Now, we can just go straight to this solution, type in the log ID and server ID, and obtain the information that we want."
"InsightOne is the main reason why we use LogMeIn. This is mostly because of log data that we are pushing tools and logs in general."
"The query mechanism for response codes and application health is valuable."
"The other nice thing about Logz.io is their team. When it comes to onboarding, their support is incredibly proactive. They bring the brand experience from a customer services perspective because their team is always there to help you refine filters and tweak dashboards. That is really a useful thing to have. Their engagement is really supportive."
"Ingesting data from various sources to monitor the log metrics of the system can always improve so that, if something goes wrong, the right teams are alerted."
"I've only been using Datadog for a few months, and at first, it was frankly overwhelming in terms of both the UI and the available capabilities."
"Datadog lacks a deeper application-level insight. Their competitors had eclipsed them in offering ET functionality that was important to us. That's why we stopped using it and switched to New Relic. Datadog's price is also high."
"Some of the interface is still confusing to use."
"I would love to see more metrics or analytics in IoT devices."
"The way data is represented can be limiting. When I first tried it out a long time ago, you could graph a metric and another metric, and they'd overlay, but you couldn't take the ratio between the two."
"The ease of implementation needs improvement."
"Datadog is so feature-rich that it is often hard to onboard new folks and tough to decide where to invest time."
"I would like granularity on alerting so we can get tentative alerts and major alerts, then break it down between the two."
"When it comes to reducing our troubleshooting time, it depends. When there are no bugs in Logz.io, it reduces troubleshooting by 5 to 10 percent. When there are bugs, it increases our troubleshooting time by 200 percent or more."
"The solution needs to expand its access control and make it accessible through API."
"I would like them to improve how they manage releases. Some of our integrations integrate specifically with set versions. Logz.io occasionally releases an update that might break that integration. On one occasion, we found out a little bit too late, then we had to roll it back."
"Capacity planning could be a little bit of a struggle."
"The price can be cheaper and they should have better monitoring."
"The solution needs to improve its data retention. It should be greater than seven days. The product needs to improve its documentation as well."
"The product needs improvement from a filtering perspective."
Datadog is ranked 3rd in Log Management with 137 reviews while Logz.io is ranked 24th in Log Management with 8 reviews. Datadog is rated 8.6, while Logz.io is rated 8.2. The top reviewer of Datadog writes "Very good RUM, synthetics, and infrastructure host maps". On the other hand, the top reviewer of Logz.io writes "The solution is a consistent logging platform that provides excellent query mechanisms". Datadog is most compared with Dynatrace, Azure Monitor, New Relic, AWS X-Ray and Elastic Observability, whereas Logz.io is most compared with Wazuh, Coralogix, Microsoft Sentinel, Splunk Enterprise Security and Grafana Loki. See our Datadog vs. Logz.io report.
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We monitor all Log Management 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.