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.
"The solution is sufficiently stable."
"The solution's SaaS model is easy to manage and works well in single- or multi-cloud environments."
"Because of our client focus, it is easy for us to sell. This is because it is easy to use and easy to set up."
"It has provided visibility with ease of implementation and allowed multiple teams to quickly onboard it."
"Thanks to the logs, we manage to make better reports through Jira and also to trace the request with more facility than we would be able to do otherwise."
"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 observability pipelines are the most valuable aspect of the solution."
"The most valuable aspect of the solution is the APM."
"Open source and user friendly."
"Real-time UDP/GELF logging and full text-based searching."
"The product is scalable. The solution is stable."
"We run a containerized microservices environment. Being able to set up streams and search for errors and anomalies across hundreds of containers is why a log aggregation platform like Graylog is valuable to us."
"The ability to write custom alerts is key to information security and compliance."
"This had increased productivity for the dev and support teams, because we are directly notifying them."
"Graylog's search functionality, alerting functionality, user management, and dashboards are useful."
"The build is stable and requires little maintenance, even compared to some extremely expensive products."
"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."
"In the past two years, there have been a couple of outages."
"The pricing should be less of a surprise."
"Managing dashboards as IaC is a bit hard to work out at times."
"It can have an artificial intelligence component. Even though I can seamlessly look at end-to-end security, it would be better to have alerts and notifications powered by an AI engine. I am not sure if they have an AI component. We have not reached out to them or looked at it, but this is something that I keep on talking about within our company in terms of features. Such a feature would be good to have, and it would further optimize my Security Ops team's abilities."
"The on-premise version is very difficult to upgrade."
"The ability to find what you are looking for when starting out could be improved."
"I'm not sure what kind of features are in the roadmap right now, but I encourage the development of features for defining your organization, and allowing the visibility of what kind of metrics you can get. Those features would be really useful for us."
"Since container orchestration systems are popular and Graylog fits the niche well, perhaps they could officially support running in docker containers on Kubernetes as a StatefulSet as a use case. That way, the declarative nature of Kubernetes config files would document their best case deployment scenario-"
"Its scalability gets complicated when we have to update or edit multiple nodes."
"Graylog needs to improve their authentication. Also, the fact that Graylog displays logs from the top down is just ridiculous."
"Elasticsearch recommendations for tuning could be better. Graylog doesn't have direct support for running the system inside of Kubernetes, so it can be challenging to fill in the gaps and set up containers in a way that is both performant and stable."
"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."
"More customization is always useful."
"Graylog can improve the index rotation as it's quite a complex solution."
Datadog is ranked 3rd in Log Management with 137 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 Elastic Observability, whereas Graylog is most compared with Grafana Loki, Wazuh, syslog-ng, Fortinet FortiAnalyzer 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.