Both of these solutions, Dynatrace and Datadog, have emerged as leaders in the IT and application performance monitoring space. Both platforms deliver cloud-based Software-as-a-Service (SaaS) offerings that continuously gauge performance and identify issues before they become full-fledged problems.
And both platforms help manage increasingly complex information technology (IT) frameworks – a growing challenge for companies. Organizations must ensure that servers, databases, applications and a vast array of other tools and resources are operating correctly and performing well at all times. Organizations that falter are at risk for glitches, breakdowns and complete failures.
As a result, infrastructure and application performance monitoring tools like Dynatrace and Datadog have emerged as mission critical requirements. Solutions that address this space deliver deep visibility into various aspects of system performance by scraping data from various sources, including logs, tags, data flows, software code and devices. They identify relationships, gauge network behavior and spot problems.
Dynatrace and Datadog also tap data analytics, machine learning and other forms of artificial intelligence to deliver broad and deep insights. The result is a unified view of resources: what’s performing well and what’s underperforming. Let’s take a look at how these two applications compare.
Also see: Real Time Data Management Trends
Dynatrace vs. Datadog: Integration Comparison
The Dynatrace solution delivers visibility into more than 600 hundred products, services and technologies through a robust set of APIs. Monitoring capabilities encompass Active Directory, Adobe Analytics, AWS, Apache, Azure, Cisco, Citrix, Linux, Docker, Drupal, Google, IBM, Microsoft, Salesforce and Slack.
There’s also support for Kubernetes, Java and a vast array of other entities. Thanks to a broader set of integrations, Dynatrace holds a slight edge in this category, though both products are likely to accommodate virtually every requirement an organization can toss at them.
The Datadog platform delivers built-in support more than 500 integrations that extend across a broad mix of systems, apps and services. Datadog offers powerful auto-discovery features that can find almost every major solution and vendor.
The list includes Active Directory, Adobe, Cisco, SAP, Akamai, Alibaba Cloud, AWS, Azure, Google, Salesforce, IBM WAS, Oracle, Okta, Zoom and Zendesk. It also accommodates Kubernetes, Java and Linux components.
Dynatrace vs. Datadog: Compare Monitoring
The point of any monitoring solution is to deliver a comprehensive view of a technology stack. Dynatrace succeeds through robust real-time and synthetic tracking. It relies on a single agent per host to collect all relevant data and metrics continuously.
The platform delivers a view into the full stack—everything from the behavior of visitors at a website to technical factors such as performance of clouds, mobile and Web APIs, DevOps automation, container functionality and ecosystem integrations. The firm’s PurePath Technology also provides distributed and automated transaction tracing and code-level visibility. This makes it possible to analyze end-to-end transactions across every tier of the stack.
Datadog’s highly flexible and easy-to-use interface delivers high quality and visually appealing dashboards and notebooks that deliver a single place to view events and data, including container and API metrics. Datadog offers broad and deep visibility into the entire stack, with granular filtering and highly detailed logging for websites, applications and various other components.
The platform also delivers excellent customization through Dashboards, Timeboards and Screenboards that provide different visualizations. All of this makes infrastructure reviews and root cause investigations much simpler. It also helps DevOps teams identify bottlenecks and problems. Finally, Datadog offers a Session Replay feature that helps troubleshoot and fix UX and other problems.
Also see: Top Business Intelligence Software
Dynatrace vs. Datadog: Performance Comparison
Dynatrace offers solutions designed for vertical industries, including airlines, healthcare, telecom, manufacturing, e-commerce, retail and financial services. It is available for Windows, Mac and Linux devices.
Because it’s a cloud platform, it’s also possible to access features from a web browser. Dynatrace provides advanced capabilities such as continuous and automated AI discovery across the full stack, including multi-cloud environments, microservices and containers. This includes automatic real-time topology and mapping with context, self-healing and automation features, and the ability to hyperscale the solution across hundreds of thousands hosts, millions of entities and even the largest and complex multi-cloud environments.
The Datadog platform delivers live process infrastructure monitoring but also supports continuously historic records, including those for retired or defunct systems. Datadog, which supports Windows, Mac and Linux devices, accommodates tens of thousands of key metrics out of the box.
Its APM component delivers end-to-end distributed tracing with minimal latency and an ultra-low error rate. Datadog also offers AI capabilities that allow it to auto-discover new components and auto-track them. Machine learning helps identify false positives and false negatives that lead to irrelevant and unnecessary alerts. Datadog delivers a variety of features and capabilities focused on infrastructure, APM, security monitoring, network monitoring, synthetic monitoring and more. The platform supports data encryption. However, it lacks some of the network access and control features that Dynatrace provides.
Dynatrace vs. Datadog: Reporting Comparison
Reporting is a critical element in Dynatrace’s infrastructure and application performance management. The platform delivers deep insights through analytics tools and reporting. It’s possible to generate reports based on specific criteria and easily share the reports via email and other messaging tools.
A dashboard displays various applications and systems, and includes a score based on the percentage of problems and failures. Teams can use this data to diagnose and address various issues and problems. The platform also offers extensive real-time notifications and alerts—with filtering capabilities. However, it lacks a re-notification feature.
Datadog offers a flexible and robust reporting framework with drag-and-drop features, including widgets and pre-designed templates to accommodate most industries and use cases. The platform also provides tools for building custom reports. A Metrics Summary page displays key performance indicators for different time frames, including hours, days and weeks. Datadog also allows users to search on various factors and indicators using tags and other criteria. It offers robust notification and alerting capabilities, including the ability to re-notify people.
Also see: What is Data Visualization
Dynatrace vs. Datadog: Compare Service and Support
The widespread popularity of Dynatrace translates into a robust and highly rated online community. There’s also an extensive online knowledge base that aids in setting up and using the platform. Dynatrace offers standard tier Web and chat support on an 8/5 basis. Its Dynatrace One Premium tier includes live phone-based in-product assistance, a dedicated product specialist manager and 24/7 continuous support. The company has high user ratings for providing service and support in a timely and efficient manner.
Datadog operates a community forum and has a comprehensive online knowledge base available for users. The latter includes documents that cover almost every aspect of the platform and various products. Support depends on the version of the software an organization uses. Free and basic versions of the company’s products are typically backed only by a discussion group. Other offerings include chat and email support. More advanced offerings include priority phone support.
Dynatrace vs. Datadog: Price Comparison
Dynatrace offers a free trial. It has a tiered pricing model that covers different service needs. For example, a digital experience monitoring package starts at $11 per license per month billed annually. It covers AIOps along with digital business analytics.
Application security starts at $12 per month and covers automatic continuous runtime analysis. Open ingestion that monitors metrics, logs, and traces in the context of a common data model costs $25 per month. Infrastructure modeling is $21 per month. It covers infrastructure monitoring, AIOps, and Digital Business Analytics.
Full stack monitoring runs $69 per month. It includes APM, infrastructure monitoring, AIOps, and Digital Business Analytics. Cloud automation starts at $0.10 per cloud automation unit. Although Dynatrace offers powerful capabilities, it tends to be pricey.
Datadog has a complex pricing model based on the specific service. For example, infrastructure has a three-tier pricing model. A free version supports up to five hosts and includes core collection and visualization features. However, it offers only a 1-day metric retention.
A Pro version costs $15 per month per host. It includes 500+ integrations, out-of-the-box dashboards and 15-month metrics retention. The Enterprise version (100 host minimum) includes machine learning-based alerts, live processes and premium support. Datadog also offers volume discounts for those requiring 500+ hosts per month. Overall, Datadog is more affordable than Dynatrace.
Also see: Top AI Software
Dynatrace vs. Datadog: Conclusion
Clearly, both Dynatrace and Datadog offer a wealth of features and capabilities that make them highly appealing – both have an impressive roster of customers.
Nevertheless, it’s important to review the various connectors and features each offers before selecting a vendor and installing a solution. In addition, pricing plans can lead to significantly different costs, and support options may or may not fit your needs. As a rule, Dynatrace is more widely adopted by large enterprise, while Datadog tends to appeal more to small and medium-sized businesses.