We performed a comparison between Datadog and Grafana Loki based on real PeerSpot user reviews.
Find out in this report how the two Log Management solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."Datadog provides tracing and logging, whereas Dynatrace focuses on tracing, and Splunk is more of a logging tool. Datadog's advantage is that we don't need two tools."
"I find the greatest feature is being able to search across logs from various microservices."
"Datadog has given us near-live visibility across our entire cloud platform."
"Most of the features in the way Datadog does monitoring are commendable and that is the reason we choose it. We did some comparisons before picking Datadog. Datadog was recommended based on the features provided."
"Overall, the Data UI and the usability of customer features continue to improve."
"The dashboards are great."
"The product has offered increased visibility via logging APM, metrics, RUM, etc."
"Datadog has so far been a breeze to use and set up."
"The most valuable features of the solution stem from the fact that it is an open-source tool that is stable and flexible."
"The tool can be used in multi-cluster environments."
"Loki also utilizes the same service discovery mechanism as used by Prometheus. So, whatever labeled metadata you see in Prometheus, you have the exact same metadata in the Loki system. Given this level of intricacy and the attempt to address these challenges, I firmly believe that Loki deserves praise for the work."
"The best feature of Grafana Loki is that it integrates well with our other tool."
"I appreciate the capability to process logs from microservices and seamlessly integrate them into Grafana."
"We are using Grafana Loki as a database for real-time metrics."
"The most valuable feature is the capability to set up alerts, which becomes necessary when we need to receive notifications for specific events."
"The effectiveness of filters is pivotal for optimizing the search process and extracting the specific information we need from the extensive log data."
"Auto instrumentation on tracing has not been very easy to find in the documentation."
"One thing we have run into is that it is so easy to add monitoring that we turn on things without really understanding the costs."
"Its pricing model can be improved. Its settings should be improved for a better understanding of billing. They should also provide some alerts when there is an increase in the usage. For example, if there is 20% more increase from one week to another, the customer should get an alert."
"I would like better navigability across pages."
"There are things about it that we would like to be fixed, such as it is taking averages of average. This results in data that we don't expect."
"The documentation could be improved regarding setting up the agent properly and debugging."
"I would like the tooling to have better integration in Slack, specifically sending out reminders to the relevant people to take breaks, do a retrospective, and specify with emojis which messages to log."
"I sometimes log in and see items changed, either in the UI or a feature enabled. To see it for the first time without proper communication can sometimes come as a shock."
"The Docker container partition feature needs improvement as they do not reuse the space and goes into a pending state."
"Visualization-wise, Grafana Loki's dashboard looks a little outdated compared to other open-source visualization tools like Chronograf."
"Enhancing speed could be a game-changer, and while it might vary depending on the application, it's a factor worth exploring."
"The product must improve its UI."
"The correlation of requests is not simple in Grafana Loki and can be improved."
"We encountered certain limitations when it came to alerting, particularly when dealing with specific data sources."
"We had a well-structured dashboard with a functional query. However, an issue arose when the Kubernetes pod restarted. The statistics from our Grafana query would reset, dropping to zero and starting anew. This was particularly noticeable with linear graphs, which are expected to show consistent growth."
"My main concern is the recommended production-grade setup. They suggest using tools like Tanka or Jsonnet. They should simplify the process to increase adoption."
Datadog is ranked 3rd in Log Management with 137 reviews while Grafana Loki is ranked 13th in Log Management with 12 reviews. Datadog is rated 8.6, while Grafana Loki 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 Grafana Loki writes "Effective for Logging, recovery from node failures is fast and single UI supports metrics, logs, and even tracing". Datadog is most compared with Dynatrace, Azure Monitor, New Relic, AWS X-Ray and Elastic Observability, whereas Grafana Loki is most compared with Graylog, Wazuh, syslog-ng, Splunk Enterprise Security and Elastic Stack. See our Datadog vs. Grafana Loki report.
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