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.
"The biggest thing I liked was the combination of all the things - monitoring, log aggregation, and profiling."
"Dashboards and their versatility are among the most valuable features."
"Its integration definitely stands out. It provides seamless monitoring of all our systems, services, apps, and whatever else we secure and monitor. Visualizations have become simpler with dashboards. We are getting visibility into systems, services, and apps stack through a single pane of glass, which is good. We are able to put logs in context."
"Datadog's seamless integration with Slack and PagerDuty helped us to receive alerts right to the most common notification methods we use (our mobile devices and Slack)."
"Datadog helps us detect issues early on and helps in troubleshooting."
"I like that you can build out a dashboard pretty quickly. There are some things that come out of the box that you don't really need to do, which is great because they're default settings."
"Datadog is providing efficiency in the products we develop for the wireless device engineering department."
"The CCM, Workflows, Logs, APM, and RUM are all useful aspects of the solution."
"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 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."
"We use the tool to track the dev and production environment."
"The query mechanism for response codes and application health is valuable."
"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 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."
"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."
"While the tool is robust with many different capabilities, users would greatly benefit from more examples in the documentation."
"Datadog has a lot of features kind of cramped into one dashboard. It's quite hard to get around what feature does exactly what. There was a steep learning curve, trying to navigate through menus."
"I would love to see more metrics or analytics in IoT devices."
"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."
"I'm still exploring the trial version, and it is fine. One thing that I haven't been able to figure out is how to retrieve a report. This is something that could be improved. I probably need to navigate to a place to access the reports."
"Since the Datadog platform has so many separate features, solving so many use cases, there are often inconsistencies in feature availability and interoperability between products."
"The solution needs to integrate AI tools."
"I found the solution to be stable, I did not experience any bugs or glitches. However, some of the managing team did."
"The price can be cheaper and they should have better monitoring."
"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."
"I would like granularity on alerting so we can get tentative alerts and major alerts, then break it down between the two."
"The product needs improvement from a filtering perspective."
"The solution needs to improve its data retention. It should be greater than seven days. The product needs to improve its documentation as well."
"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."
"Capacity planning could be a little bit of a struggle."
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.