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.
"Datadog has made it much easier to have a central place for people to look for logs and made it much easier to notify them of any elevated error rates or failures."
"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 dashboards and the performance of the software have been great."
"Datadog agents act as an integration to different services, providing easy access and management."
"Using the data, our operation teams works with the dashboards to get their statistics, analytics, etc."
"The biggest thing I liked was the combination of all the things - monitoring, log aggregation, and profiling."
"Its integration is most valuable because you can integrate it with various service providers such as AWS, .Net, etc."
"The service catalog helped improve our organization by giving a good view of the flow for our microservices applications."
"The solution's initial setup process was straightforward since we were getting enough support from Honeycomb.io's team."
"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 would like better navigability across pages."
"We need to learn more about the session reply feature inside of DD."
"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."
"Delta traces on the Golang profiler are extremely expensive concerning memory utilization."
"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."
"Sometimes it’s difficult to customize certain queries to find specific things, specifically with the logging solution."
"The real issue with this product is cost control."
"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.
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