Users reported that Datadog excels in customer service and support, with prompt assistance and knowledgeable staff. ROI was deemed highly positive, with improvements in monitoring and troubleshooting capabilities. Datadog users seek enhanced customization options and better integration capabilities. Honeycomb.io offers advanced visualization capabilities and high cardinality query support. Users appreciate the platform's collaborative nature but call for better integrations, simplified pricing, and improved documentation.
Features: Datadog excels in comprehensive monitoring and customizable dashboards, with seamless integrations. Honeycomb.io stands out for advanced visualization and detailed insights with high cardinality query support. Users appreciate each platform's collaboration features for efficient teamwork.
Pricing and ROI: Datadog's setup cost is minimal and praised for its transparency and flexibility in pricing. Honeycomb.io also offers a competitive pricing with straightforward setup cost and licensing structure, making it easy to budget for. Datadog's ROI is praised for significant monitoring and troubleshooting improvements, while Honeycomb.io's ROI highlights system performance enhancements and powerful querying capabilities, leading to increased productivity.
Room for Improvement: Datadog's room for improvement lies in enhanced customization options for dashboard layouts, better integration capabilities, and improved alerts and notifications setup. Meanwhile, Honeycomb.io needs more usability, customization choices, smoother integrations, and enhanced overall performance.
Deployment and customer support: The reviews on Datadog indicate a range of timeframes for deployment and setup, with potential confusion on whether they are distinct phases. In contrast, feedback on Honeycomb.io shows a clearer distinction between deployment and setup timelines, emphasizing the need for careful consideration in evaluating implementation durations. Datadog has satisfied customers with their prompt and knowledgeable customer service, while Honeycomb.io's team stands out for their helpfulness, clear communication, and expert assistance. Both companies excel in addressing issues effectively.
The summary above is based on 195 interviews we conducted recently with Datadog and Honeycomb.io users. To access the review's full transcripts, download our report.
"We have a better grasp of what is occurring during the deployment cycle. If something fails, we have an idea what has failed, where it has failed, and how it failed to better mitigate the situation."
"It is easy to navigate the menu and create tests."
"I don't have to worry about upgrades with the AWS version."
"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."
"It is great that creating an incident is possible from Slack while having all the relevant data in Datadog."
"Using the data, our operation teams works with the dashboards to get their statistics, analytics, etc."
"We have been able to set very specific CPU and memory alerts, at the very base level, then we started to pull real business value, like 99th percentile response rates for our API calls."
"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."
"The solution's initial setup process was straightforward since we were getting enough support from Honeycomb.io's team."
"Datadog needs more local Asia-Pacific support, and if they don't have a SaaS solution in Asia-Pacific, they should offer an on-prem version. I'm told that's not possible."
"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."
"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 correlation between the logs and the metrics needs improvement as most cases, we might use another logging tool (that is cheaper in cost) which we then have to link together."
"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."
"Sometimes, it takes a long time to load the dashboard if we have many charts."
"Datadog is expensive."
"It would be nice to be able to graph metrics by excluding certain tags (like you can do in monitors)."
"The process of log scraping gets delayed on Honeycomb.io. At times, it gives false alerts to the application team."
Datadog is ranked 1st in Application Performance Monitoring (APM) and Observability with 137 reviews while Honeycomb.io is ranked 37th in Application Performance Monitoring (APM) and Observability with 1 review. Datadog is rated 8.6, while Honeycomb.io 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 Honeycomb.io writes "A valuable solution for application teams to identify downtime and SLO-related issues". Datadog is most compared with Dynatrace, Azure Monitor, New Relic, AWS X-Ray and Elastic Observability, whereas Honeycomb.io is most compared with Grafana, Sentry, Chronosphere, Azure Monitor and New Relic.
See our list of best Application Performance Monitoring (APM) and Observability vendors.
We monitor all Application Performance Monitoring (APM) and Observability 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.