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.
"The application performance monitoring is pretty good."
"It has saved us a lot of trouble in implementation."
"The most valuable aspect is for us to have everything in one place."
"The visibility into our network has allowed for quick diagnosis of failures, identification of underutilized or over-utilized resources, and allowed for cloud cost optimization opportunities."
"The solution has helped out organization gain improved visibility."
"It has a high-level insight into the infrastructure model of the application and provides important detailed data on the host and metrics, which is the main concern of our customers."
"It has enhanced the performance of my team."
"The web app has a real-time support chat window in which a support engineer is chatting with you within a minute."
"The solution's initial setup process was straightforward since we were getting enough support from Honeycomb.io's team."
"If there were a more cost-effective manner of deploying the tool, we'd be more likely to adopt it more widely."
"It does not have the best interface."
"It is very difficult to make the solutions fit perfectly for large organizations, especially in terms of high cardinality objects and multi-tenancy, where the data needs to be rolled up to a summarized level while maintaining its individual data granularity and identifiers."
"Datadog isn't as mature as some of the established players like Dynatrace or Splunk. It's a new product, so they are constantly releasing new features, and I don't have much to complain about."
"I find the training great. That said, it is set for the LCD (lowest common denominator). Of course, this is very helpful to sell the product, yet, to really utilize the product, you need to get more detailed."
"Graph filters for logs need to be set manually which works well for JSON but not for unstructured logs."
"The on-premise version is very difficult to upgrade."
"While the tool is robust with many different capabilities, users would greatly benefit from more examples in the documentation."
"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, New Relic and Azure Monitor.
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.