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.
"We rely heavily on the API crawlers that Datadog uses for cloud integrations. These allow us to pick up and leverage the tags teams have already deployed without having also to make them add them at the agent level."
"We've found it most useful for managing Rstudio Workbench, which has its own logs that would not be picked up via Cloudwatch."
"APM is great and has provided low-effort out-of-the-box observability for various services."
"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 brings in observability, monitoring, and alerting capabilities - all of which we need to operate at scale."
"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."
"The solution is sufficiently stable."
"The performance of Datadog is good."
"I am very proud of how very stable the solution is."
"Storing logs in Elasticsearch means log retrieval is extremely fast, and full text search is available by default."
"It is used as a log manager/SIEM. It provides visibility into the infrastructure and security related events."
"We have scaled from a single machine installation (a VM with a Graylog + ES + MongoDB) to (2 Graylog + 2 ES + 3 MongoDB). This was done smoothly with a minimal impact on logging."
"The solution's most valuable feature is its new interface."
"The best feature of Graylog is the Elasticsearch integration. We can integrate and we can run filters, such as an event of interest, and those logs we can send to any SIEM tool or as an analytic. Additionally, there are clear and well-documented implementation instructions on their website to follow if needed."
"One of the most valuable features is that you are able to do a very detailed search through the log messages in the overview."
"I like the correlation and the alerting."
"The pricing model could be simplified as it feels a bit outdated, especially when you look at the billing model of compute instances vs the containers instances."
"It could probably be a little bit of a better user experience."
"While the tool is robust with many different capabilities, users would greatly benefit from more examples in the documentation."
"I would like testing for data in the future."
"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."
"Datadog is expensive."
"This service could be less costly."
"Managing dashboards as IaC is a bit hard to work out at times."
"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-"
"With technical support, you are on your own without an enterprise license."
"Dashboards, stream alerts and parsing could be improved."
"There should be some user groups and an auto sign-in feature."
"Its scalability gets complicated when we have to update or edit multiple nodes."
"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."
"I would like to see some kind of visualization included in Graylog."
"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."
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.