Datadog vs. New Relic: A Comprehensive Comparative Analysis

Are building new software applications and deploying them quickly your go-to business strategy? Well, then, I’m sure that you would seek a solution to dodge the bullets of system downtimes, performance bottlenecks, and security vulnerabilities. That is, all of which can lead to revenue loss and customer dissatisfaction. The key to avoiding these challenges lies in effective application monitoring and management. This is where Datadog and New Relic, two industry leaders, come into play, each offering powerful solutions to keep your applications running seamlessly.

Although both the platforms provide similar core functionalities, their unique features and user experiences set them apart. This blog will help understand the perks and drawbacks of both the platforms across several factors, so that, you can decide which tool best suits your analytical needs.

So, let’s get started!

Platform Capabilities

Fig: Features of Datadog and New Relic

Hope you’ve got an initial level overview! Now, let’s delve deeper to know how they differ based on several factors.

Factor 1: Ease of Integration and Deployment

a. New Relic:

• Account Setup: You can use a free-forever account, which allows full access to all features without time constraints.
• Installation: The guided installation process is straightforward, involving a code snippet for the infrastructure agent and logging setup.

b. Datadog:

• Account Setup: You can opt for a 14-day free trial, getting yourself full access to explore its features.
• Installation: The deployment process is simple, requiring just a bash command to install Datadog’s infrastructure monitoring agent.

Factor 2: Application Monitoring (APM)

a. New Relic APM:

• Auto-instrumentation: Supports eight languages including Java, .NET, Node.js, PHP, Python, Ruby, Go, and C/C++.
• Tracing and Sampling: Offers distributed tracing and sampling for various tech stacks.
• Integration: Correlates tracing data with infrastructure and user monitoring, providing a cloud-native, scalable experience.

Here’s a screenshot showcasing New Relic’s APM:

Fig: New Relic’s APM

b. Datadog APM:

• Network Tracing: Tracks user interactions from sessions to databases and links these with infrastructure data.
• Trace Capture: Captures all traces from the past 15 minutes, focusing on errors and slow responses.
• Code Analysis: Analyzes individual functions to identify sluggish requests.

Here’s a screenshot showcasing Datadog’s APM:

Fig: Datadog’s APM

Factor 3: Infrastructure Monitoring

a. New Relic:

• Performance Insights: Connects host performance with configuration changes and provides integration with AWS, GCP, Azure, Kubernetes, etc.
• Troubleshooting: Links server-side metrics to application performance.

Here’s a screenshot showcasing New Relic’s monitoring process:

Fig: New Relic’s monitoring process

b. Datadog:

• Visualization: Features a Host Map for visualizing all hosts and a Container Map for real-time container monitoring.
• Tagging: Allows tagging and metrics association for comprehensive visibility.

Here’s a screenshot showcasing Datadog’s monitoring process:

Fig: Datadog’s monitoring process

Factor 4: Network Monitoring

a. New Relic:

• Dashboards: Provides pre-configured dashboards for major cloud services with dynamic alerting features.

b. Datadog:

• Data Insights: Offers detailed network flow data within multi-cloud environments and aggregates data via tags.

Factor 5: Log Management

a. New Relic:

• Log Collection: Automatically collects logs and provides search capabilities using Lucene and NRQL.
• Visualization: Log data is displayed in a user-friendly tab.

Note: To monitor custom log files with New Relic, you’ll need to set up log management and ensure that your log data is being ingested and visualized in New Relic’s platform. Here’s a straightforward guide to help you get started:

1. Setting Up New Relic Logs

First, ensure that New Relic Logs is enabled in your New Relic account. This feature is typically included in the New Relic Observability suite, but make sure you have the appropriate plan.

2. New Relic Agent Installation and Configuration

To transmit log data to New Relic, you must install and set up a log forwarder agent. New Relic offers multiple methods for log forwarding, such as:

• New Relic Logs Ingestion Agent: This agent is a lightweight, open-source log forwarder specifically for New Relic.
• Fluentd/Fluent Bit: These are popular log collectors that can be configured to send logs to New Relic.
• Logstash: Another option for forwarding logs from various sources.

b. Datadog:

• Log Collection: Requires manual activation for automatic log collection.
• Pattern Detection: Offers log pattern detection and visualization tools. It integrates with cloud storage for long-term log retention.

Factor 6: Incident Management and Alerting

a. New Relic:

• Automatic Alerts: Provides auto-generated UI alerts for key performance metrics, known as the Four Golden Signals. They are as follows:

  1. Latency
  2. Traffic
  3. Errors
  4. Saturation

Here are the two alert types:

• NRQL Alerts: You can create custom alerts using NRQL (New Relic Query Language) to define complex conditions.
• Infrastructure Alerts: These are tied to New Relic’s infrastructure monitoring, covering metrics like CPU, memory, and disk usage.

b. Datadog:

• Custom Alerts: Datadog allows you to set up alerts based on metrics collected from various sources such as servers, applications, databases, and custom metrics. You can define thresholds and conditions for when alerts should be triggered based on these metrics.

Here are its three alert types:

• Metric Alerts: Based on time-series metrics with various aggregation options.
• Log Alerts: These can be triggered based on log patterns or content.
• Trace Alerts: Based on APM traces and performance metrics.

Factor 7: Kubernetes Integration

a. New Relic:

• Monitoring: Provides visibility into Kubernetes clusters, nodes, namespaces, and app performance.
• Alerts: Delivers comprehensive performance metrics and sends alerts based on customized thresholds.
• Visualization: Provides rich dashboards for performance insights.

b. Datadog:

• Comprehensive Monitoring: Provides extensive monitoring for clusters, nodes, pods, and containers with metrics on resource utilization.
• Logging & Tracing: Integrates logs and traces for a holistic view.
• Customization: Highly customizable dashboards for Kubernetes metrics.

Factor 8: Artificial Intelligence

a. New Relic AI:

• Capabilities: Converts natural language into queries, reviews logs, identifies anomalies, and delivers insights into stack traces. Interactive AI helps in troubleshooting and exploring data.

  New Relic AI has undergone extensive training to engage in conversations with engineers, addressing frequently asked questions and employing straightforward language. Imagine you operate an e-commerce platform and notice alerts indicating a slowdown in response times for your Checkout service.

  Should you find yourself short on time to investigate the matter yourself, you may simply query New Relic AI with questions such as “What’s causing the issue?” Or “What tasks should I prioritize today?”

  So, it is designed to pinpoint the root cause of issues in your system and support data analysis with detailed charts and tables.

Here’s a sample question and the output provided by AI:

Question: What is the average performance of my application?

Fig: New Relic AI Output

b. Datadog AI:

• Bits AI: Currently in beta, Datadog is working on integrating AI to enhance its monitoring capabilities.

Factor 9: Cloud SIEM (Cloud-based security information and event management)

a. New Relic: Does not currently offer a Cloud SIEM feature.

b. Datadog: Offers a robust Cloud SIEM solution for real-time detection, alerting, and compliance reporting.

Factor 10: Pricing

a. New Relic pricing:

• Free Tier: Offers a generous free subscription with one full platform user and 100GB of ingested data.

b. Datadog pricing:

• Free Tier: Provides a 14-day free trial with access to all features.

Therefore, both Datadog and New Relic excel in various areas. Feel free to navigate through these pointers to make the right decision while opting for any of the two:

• For improved signal correlation and advanced Cloud SIEM, Datadog is the better choice.
• For a more generous free tier and a comprehensive monitoring experience without worrying about usage costs, New Relic stands out.
• For granular data controls and advanced log pattern detection, Datadog offers superior options.
• For real-user monitoring and AI assistance, New Relic provides more comprehensive app monitoring tools.

So, the best choice depends on your specific requirements and the features that align with your monitoring needs.

Reach out to Nitor Infotech today to develop a strong application performance monitoring framework and build top-tier software products in 2024.