We performed a comparison between Datadog and Graylog based on our users’ reviews in five categories. After reading all of the collected data, you can find our conclusion below.
Features: Datadog users like its customizable displays, error tracking, and advanced AI/ML capabilities. Graylog stands out with its exceptional search functions, seamless integration with Elasticsearch, and real-time data access. Datadog could enhance its usability and reduce its learning curve. Users said integration was another pain point. Graylog could benefit from additional customization options and an improved rule-creation process.
Service and Support: While many users spoke highly of Datadog’s support team, others reported slow support, especially in the Asia-Pacific region. Graylog's customer service is generally well-regarded, with reviewers noting effective solutions and satisfactory experiences. While response times may differ, Graylog's support is considered superior compared to that of other products.
Ease of Deployment: Datadog’s setup is considered straightforward, and users often receive help from a partner or vendor. Some Graylog users said the setup was easy. Other reviewers faced challenges, but these were easily resolved with help from the vendor’s support staff. Graylog is easier to set up in smaller environments, but it could get complicated in large clusters.
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. Graylog offers an enterprise edition and an open-source option with a daily capacity restriction. Some users said that data costs can be expensive.
ROI: Users said Datadog saved them time and improved visibility into security blind spots. Graylog can offer some cost savings. The precise ROI may vary depending on the organization’s size and use case.
"It is easy to implement and scale applications with standardized visibility, monitoring and alerting"
"I find the greatest feature is being able to search across logs from various microservices."
"The ingestion points are unlimited and support customization. We haven't had anything yet that we haven't been able to integrate with it."
"It lets us react more quickly to things going wrong. Whereas before, it might have been 30 minutes to an hour before we noticed something going on, we will know within a minute or two if something is off, which will let us essentially get something back up and running faster for our customers, which is revenue."
"We like the distributed tracing and flame graphs for debugging. This has been invaluable for us during periods of high traffic or red alert conditions."
"The solution allows flexibility and heightened observability for presenting data, creating indicators, and setting service-level objectives."
"The ability to easily drill down into log queries quickly and efficiently has helped us to resolve several critical incidents."
"APM is great and has provided low-effort out-of-the-box observability for various services."
"I like the correlation and the alerting."
"The product is scalable. The solution is stable."
"UDP is a fast and lightweight protocol, perfect for sending large volumes of logs with minimal overhead."
"The build is stable and requires little maintenance, even compared to some extremely expensive products."
"Open source and user friendly."
"It is used as a log manager/SIEM. It provides visibility into the infrastructure and security related events."
"The solution's most valuable feature is its new interface."
"I am very proud of how very stable the solution is."
"Sometimes it’s difficult to customize certain queries to find specific things, specifically with the logging solution."
"Deploying the agents is still very manual."
"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."
"Lately, chat support has a longer waiting time."
"The more tools that they can build that allow you to run AWX playbooks, or other similar fixes, would benefit clients greatly."
"The menu on the left is pretty dense (and I know it has to be). I never knew about the cmd+k functionality until recently. It would be helpful to offer more tips/cheat sheets to see handy shortcuts like that."
"The product is quite complex, and there are so many features that I either didn't know about or wasn't sure how to use."
"Even though it is powerful on its own, the UI-based design lacks elegance, efficiency, and complexity."
"The infrastructure cost is the main issue. I like the rest. If the infrastructure costs could be lower, it would be fantastic."
"We ran into problems with Elasticsearch throwing a circuit-breaking exception due to field data size being too large. It turned out that the heap size directly impacted this size in a high-throughput environment, causing unexplained instability in Graylog. We were able to troubleshoot on the Elasticsearch size, but we should have been able to reference some minimum requirements for Graylog to know that our settings weren't sufficient."
"I would like to see some kind of visualization included in Graylog."
"I hope to see improvements in Graylog for more interactivity, user-friendliness, and creating alerts. The initial setup is complex."
"Over six months, I had two similar issues where searches were performed on field "messages". It exhausted all the memory of the ES node causing an ES crash and a Graylog halt."
"The biggest problem is the collector application, as we wanted to avoid using Graylog Collector Sidecar due to its architecture."
"Lacks sufficient documentation."
"I would like to see a default dashboard widget that shows the topology of the clusters defined for the graylog install."
Datadog is ranked 2nd in Log Management with 136 reviews while Graylog is ranked 11th in Log Management with 18 reviews. Datadog is rated 8.6, while Graylog is rated 8.0. The top reviewer of Datadog writes "Very good RUM, synthetics, and infrastructure host maps". On the other hand, the top reviewer of Graylog writes "Great detailed search features and easy Java integration, but needs improvement in integration with Python". Datadog is most compared with Dynatrace, Azure Monitor, New Relic, AWS X-Ray and AppDynamics, whereas Graylog is most compared with Grafana Loki, Wazuh, syslog-ng, Splunk Enterprise Security and ManageEngine Log360. See our Datadog vs. Graylog 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.