Datadog APM and Dynatrace are sometimes compared for numerous use cases in APM and Observability. We have a detailed features table below. You can also customize your requirements and get expert ratings comparing these two solutions against hundreds of data points across Monitoring, Problem Resolution, Pricing, Use Case Fit, Instrumentation, Integration, Observability and Compliance.
Datadog has been at the forefront of cloud monitoring for cloud-native companies. Its Application Performance Monitoring (APM) service is part of an extensive portfolio of complementary monitoring and observability tools. By capturing traces across various layers and services, Datadog APM provides developers with deep insights into their applications' performance, allowing for more effective troubleshooting and performance optimization.
Dynatrace provides an APM that supports multiple languages, application architectures, cloud, on-premises or hybrid, enterprise applications, SaaS monitoring, etc. It provides real-time visibility into microservice-based environments and automatically discovers and monitors microservice workloads running inside containers on Kubernetes. It also provides monolith and mainframe monitoring, database monitoring, application monitoring, and many other services for end-to-end visibility.
Customize these feature priorities in Taloflow and get expert ratings for your exact use case.
| Feature | Dimensions | Description | Datadog | Dynatrace |
|---|---|---|---|---|
| AI Copilot |
|
AI-powered assistance for querying and insights. | Great | Good |
| AI Stack Monitoring |
|
Provides specialized insights for the AI application stack. | Great | Good |
| Automated, Robust and Comprehensive Topology and Dependency Mapping |
|
Has a relationship engine that automatically calculates the relationships and dependencies for each unit of work. | Good | Great |
| Comprehensive and Integrated Metrics, Logs and Tracing under Developer Control |
|
Allows developers to have control over instrumenting their code. | NA | NA |
| High Cardinality Analytics at Scale |
|
Provides fields to help identify the precise nature or source of degradation and errors, even in scaled-up environments with a very high number of events. | Good | Good |
| Robust and Mature Observability Platform |
|
The solution is closer than most at offering automated and comprehensive collection of code profiles, metrics, logs, traces and dependencies for every unit of work in the application for most, if not all, use cases. | Good | Good |
| Very Flexible Custom Dashboarding |
|
A wide range of custom views are possible to share across teams. | Great | Great |
| Visible Metrics in <1 Second |
|
Delivers metrics in the UI or dashboard in near real-time. | NA | NA |
| Consumption (Data Volume) Based Pricing |
|
Rather than billing by host, CPU or core, the service will primarily bill based on the volume of data ingested. | NA | NA |
| Lowest Price (Cost) Solution |
|
The lowest cost solution for your use case even if it is not the most functionally-rich. | Great | NA |
| AWS EKS |
|
None | Great | Great |
| AlertOps |
|
None | NA | Great |
| Atlassian Jira |
|
None | Great | Great |
| Azure AKS |
|
None | Great | Great |
| Google Cloud GKE |
|
None | Great | Great |
| Microsoft Teams |
|
None | Great | NA |
| Open Source Kubernetes |
|
None | Great | Great |
| OpenShift |
|
None | Great | Good |
| OpsGenie |
|
None | Great | Great |
| PagerDuty |
|
None | Great | Great |
| Platform 9 |
|
None | NA | NA |
| Rancher |
|
None | Great | Great |
| ServiceNow |
|
None | Good | Good |
| Slack |
|
None | Good | NA |
| Splunk On-Call |
|
None | Great | Great |
| Enterprise SSO/SAML |
|
Offers SSO/SAML 2.0 to its customers. | Great | Great |
| FedRAMP |
|
Ensures that the government security requirements outlined in NIST 800-53 are met and supplemented by the PMO of FedRAMP. | NA | NA |
| GDPR |
|
Regulation on data protection and privacy of the data tied to citizens and residents of EU countries. | Great | Great |
| HIPAA |
|
Demonstrates that security and privacy requirements are met for the storing and processing of protected health information (PHI and e-PHI). | Great | Great |
| ISO 27001 |
|
Standard for information security management systems. | Great | NA |
| ISO 27017 |
|
Standard for information security management systems. | Great | NA |
| ISO 27018 |
|
Standard for information security management systems. | Great | NA |
| PCI DSS |
|
Standard that ensures consistent practices are met for data security in the payments card industry. | UNKNOWN | UNKNOWN |
| Role-based Access Control (RBAC) |
|
The organization can set up advanced access limits for individuals based on their role and filter queries for performance monitoring. | NA | NA |
| SOC 2 Type 1 |
|
Standard promoted by the American Institute of CPAs that ensures the integrity and privacy of customer data. | NA | NA |
| SOC 2 Type 2 |
|
Standard promoted by the American Institute of CPAs that ensures the integrity and privacy of customer data. | NA | NA |
| AWS Monitoring |
|
Monitor the health, performance, and security of your AWS resources and applications. | Great | Great |
| Azure Monitoring |
|
Monitor the performance and availability of your Azure applications and resources. | Great | Great |
| Google Cloud Platform Monitoring |
|
Monitor the health, performance, and security of your Google Cloud Platform resources and applications. | Great | Great |
| Kubernetes Monitoring |
|
Monitor the health and performance of your Kubernetes clusters and applications deployed on Kubernetes. | Great | Good |
| Leader in Cloud Infrastructure Monitoring (not APM or Observability) |
|
Recognized as a Leader in Cloud Infrastructure Monitoring by the big analyst firms. | Great | Good |
| On-Premises Monitoring |
|
Monitor the health, performance, and security of your on-premises infrastructure and applications. | Great | Great |
| Red Hat OpenShift Monitoring |
|
Monitor the health and performance of your Red Hat OpenShift clusters and applications deployed on OpenShift. | NA | NA |
| Session Replay |
|
View recordings of user interactions with your applications. | NA | NA |
| User Experience Monitoring |
|
Ensures the seamless experience of users interacting with your applications. | Good | Great |
| .NET Code Profiling Support |
|
Understand the resource-consumption and performance of your .NET code. | Good | Good |
| .NET Logging Support |
|
Capture log events for your application written in .NET code. | Great | Great |
| .NET Metrics Support |
|
Track metrics for your system and application written in .NET code. | Great | Good |
| .NET Tracing Support |
|
Trace transactions for your application written in .NET code. | Great | Good |
| C/C++ Code Profiling Support |
|
Understand the resource-consumption and performance of your C/C++ code. | NA | Great |
| C/C++ Logging Support |
|
Capture log events for your application written in C/C++ code. | NA | Good |
| C/C++ Metrics Support |
|
Track metrics for your system and application written in C/C++ code. | NA | Great |
| C/C++ Tracing Support |
|
Trace transactions for your application written in C/C++ code. | Great | Great |
| Continuous Profiling (Capture Code Profile for Every Trace/Transaction) |
|
Code profiling provides the insights to improve efficiency (including optimizing cloud cost) and debug performance regressions. | Great | Great |
| Data Recommendations |
|
Provides assistance in identifying uninstrumented services and vulnerabilities. | Great | Great |
| Go Code Profiling Support |
|
Understand the resource-consumption and performance of your Go code. | Great | Great |
| Go Logging Support |
|
Capture log events for your application written in Go code. | Great | Good |
| Go Metrics Support |
|
Track metrics for your system and application written in Go code. | Great | Good |
| Go Tracing Support |
|
Trace transactions for your application written in Go code. | Good | Good |
| Java Code Profiling Support |
|
Understand the resource-consumption and performance of your Java code. | Good | Great |
| Java Logging Support |
|
Capture log events for your application written in Java code. | Great | Good |
| Java Metrics Support |
|
Track metrics for your system and application written in Java code. | Great | Great |
| Java Tracing Support |
|
Trace transactions for your application written in Java code. | Great | Great |
| Language Independent Agent with Dynamic Instrumentation |
|
The agent will monitor your hosts, logs, apps, containers, etc. without any configuration necessary. | NA | Great |
| Node.js Code Profiling Support |
|
Understand the resource-consumption and performance of your Node.js code. | Great | Great |
| Node.js Logging Support |
|
Capture log events for your application written in Node.js code. | Good | Good |
| Node.js Metrics Support |
|
Track metrics for your system and application written in Node.js code. | Good | Good |
| Node.js Tracing Support |
|
Trace transactions for your application written in Node.js code. | Good | NA |
| Open Platform Supporting Third Party Agents (OTEL/Prometheus) |
|
Supports Prometheus and provides more portability if ever you want to change your observability stack by instrumenting your code using the OTEL open source protocol. | Good | NA |
| PHP Code Profiling Support |
|
Understand the resource-consumption and performance of your PHP code. | Good | Great |
| PHP Logging Support |
|
Capture log events for your application written in PHP code. | Good | Good |
| PHP Metrics Support |
|
Track metrics for your system and application written in PHP code. | NA | Great |
| PHP Tracing Support |
|
Trace transactions for your application written in PHP code. | Great | Good |
| Perl Code Profiling Support |
|
Understand the resource-consumption and performance of your Perl code. | Great | NA |
| Perl Logging Support |
|
Capture log events for your application written in Perl code. | Great | Good |
| Perl Metrics Support |
|
Track metrics for your system and application written in Perl code. | Great | NA |
| Perl Tracing Support |
|
Trace transactions for your application written in Perl code. | Good | NA |
| Python Code Profiling Support |
|
Understand the resource-consumption and performance of your Python code. | Good | Poor |
| Python Logging Support |
|
Capture log events for your application written in Python code. | Good | NA |
| Python Metrics Support |
|
Track metrics for your system and application written in Python code. | Good | NA |
| Python Tracing Support |
|
Trace transactions for your application written in Python code. | Great | Great |
| Ruby Code Profiling Support |
|
Understand the resource-consumption and performance of your Ruby code. | Good | Good |
| Ruby Logging Support |
|
Capture log events for your application written in Ruby code. | Great | NA |
| Ruby Metrics Support |
|
Track metrics for your system and application written in Ruby code. | Great | Great |
| Ruby Tracing Support |
|
Trace transactions for your application written in Ruby code. | Great | Great |
| Rust Code Profiling Support |
|
Understand the resource-consumption and performance of your Rust code. | NA | Great |
| Rust Logging Support |
|
Capture log events for your application written in Rust code. | NA | Good |
| Rust Metrics Support |
|
Track metrics for your system and application written in Rust code. | NA | NA |
| Rust Tracing Support |
|
Trace transactions for your application written in Rust code. | Good | Good |
| Scala Code Profiling Support |
|
Understand the resource-consumption and performance of your Scala code. | NA | Great |
| Scala Logging Support |
|
Capture log events for your application written in Scala code. | NA | Great |
| Scala Metrics Support |
|
Track metrics for your system and application written in Scala code. | NA | NA |
| Scala Tracing Support |
|
Trace transactions for your application written in Scala code. | NA | NA |
| eBPF Agent |
|
Extended Berkeley Packet Filter (eBPF) is like a sandbox that makes instrumentation more convenient, but is restricted to recent Linux kernels. | Good | NA |
| Accurate AI-based Problem Detection and Root Cause |
|
AI-based root cause analysis enables you to resolve problems to reduce mean time to resolution (MTTR). | Great | Great |
| Automated Problem Resolution |
|
The service automatically detects and resolves incidents, and typically generates post-mortems for record-keeping. | NA | Great |
| Available as a SaaS |
|
Provides a hosted version of the platform. | Good | Great |
| Available as an On-Premise/Self-hosted Installation |
|
Allows you to use the platform on-prem or in hybrid environments. | NA | Great |
| Enterprise-grade Customer Acquisition and Support |
|
The vendor's customer acquisition and support teams are oriented towards enterprise customers. | Great | Great |
| Enterprise-grade Product Suitable for Complex Hybrid Environments |
|
The platform comes with a number of advanced features and capabilities for hybrid environments, across monoliths, SOA and microservice-based architectures. | NA | Great |
| Leader in APM |
|
Recognized as a Leader in APM by the big analyst firms. | Good | Great |
| Suitable for Diverse Application Architectures |
|
Can cover a wide range of architectures and combinations, including microservices, SOA, monolith, N-tier, and hybrid. | Great | Great |
| Suitable for Purely Modern Microservice Architectures |
|
Focussed on the unique debugging needs of microservice-based architectures, which consist of loosely-coupled and independent services. | Great | Great |
| Well-suited to Large Enterprise IT Operations Support Teams |
|
The platform is suitable for enterprise companies with dedicated IT Operations teams. | Great | Great |
| Well-suited to Small/Midsize Cloud/SRE Teams |
|
The platform is suitable for scaleup tech companies with dedicated DevOps and SRE teams. | Great | Great |
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