How would ChatGPT compare two top observability platforms Datadog vs New Relic?
- Features: Datadog and New Relic offer similar features such as monitoring of infrastructure, applications, and logs. However, Datadog offers more extensive tracing capabilities, including distributed tracing across multiple services, and anomaly detection with machine learning. New Relic, on the other hand, provides more detailed insights into end-user experience, including real user monitoring (RUM) and synthetic monitoring.
- Pricing: Datadog pricing is based on the volume of data ingested, while New Relic pricing is based on the number of hosts monitored. This means that Datadog may be more cost-effective for companies with a large volume of data to monitor, while New Relic may be more affordable for smaller organizations with a limited number of hosts.
- Integrations: Both tools have extensive integrations with popular cloud services, but Datadog has a broader range of integrations, including more than 450 integrations, while New Relic has around 200. Additionally, Datadog has a better ability to integrate with legacy on-premises systems.
- User interface: Datadog has a more modern and intuitive user interface, while New Relic has a more traditional and sometimes cluttered UI.
- Support: Both tools offer robust support options, but Datadog has a reputation for having more responsive customer service.
Ultimately, the choice between Datadog and New Relic will depend on your specific needs, budget, and preferences.
Much of the information about New Relic is outdated, showing clearly ChatGPT’s limitation on knowledge after 2021. Since then, New Relic has transitioned to a more customer-friendly consumption model based on data ingestion (pay only what you use) and now has over 500 integration in their Instant Observability library, while simultaneously resulting in lower customer fees than Datadog. ChatGPT might be on the fence about which is the better choice, but we’re convinced it’s New Relic.