Datadog vs Splunk

Overview of Datadog Observability Platform

Datadog Observability Platform
Figure 1.0 | Datadog platform home page

Datadog is an agent-based observability service for cloud-scale applications. It provides real-time monitoring services for cloud applications, servers, databases, tools, and other services, through a SaaS-based data analytics platform. Datadog brings together end-to-end traces, metrics, and logs to make your applications, infrastructure, and third-party services entirely observable. These capabilities help businesses secure their systems, avoid downtime, and ensure customers are getting the best user experience.

Datadog was named Leader in the 2022 Gartner Magic Quadrant for Application Performance Monitoring (APM) and Observability.

Some of the key observability products and services offered on the Datadog SaaS-based platform include:

  • Application Performance Monitoring (APM) Provides end-to-end distributed tracing from browser and mobile apps to databases and individual lines of code.
  • Infrastructure Monitoring Provides metrics, visualizations, and alerting to ensure your engineering teams can maintain and optimize your cloud or hybrid environments.
  • Network Performance Monitoring Provides full visibility into every network component that makes up your on-prem, cloud, and hybrid environments, with little to no overhead.
  • Real User Monitoring (RUM) Provides insight into your application’s frontend performance from the perspective of real users.
  • Synthetic Monitoring: Allows you to create code-free tests that proactively simulate user transactions on your applications and monitor key network endpoints across various layers of your systems.
  • Log Management & Analytics Unifies logs, metrics, and traces in a single view, giving you rich context for analyzing log data.

With more than 600 built-in integrations, Datadog allows you to see across all your systems, apps, and services while aggregating metrics and events across the full DevOps stack. A free 14-day-trial with full access to all the features is available for download. After that, the software is generally sold through monthly subscription plans based on hosts, events, or logs.

Overview of Splunk Observability Cloud

Splunk is an enterprise-ready security and observability platform that provides searching, monitoring, and analyses of machine-generated data via a Web-style interface. Splunk provides deep visibility into applications and infrastructure components’ performance, including the ability to capture, index and correlate real-time data in a searchable repository, from which it can identify data patterns, generate graphs, reports, and alerts that help to diagnose problems and provide intelligence for business operations. Splunk was named Visionary in the 2022 Gartner Magic Quadrant for Application Performance Monitoring (APM) and Observability.

Splunk Observability Cloud
Figure 2.0 | A high-level view of Observability Cloud products and services | Credit: Splunk

The Splunk Observability Cloud provides full-fidelity monitoring and troubleshooting across infrastructure, applications, and user interfaces, in real-time and at any scale. Splunk Observability Cloud’s suite of products and features enable you to quickly and intelligently respond to outages and identify root causes, while also giving you the data-driven guidance you need to optimize performance and productivity.

The services offered on Splunk Observability Cloud include: 

  • Splunk Infrastructure Monitoring Gain insights into and perform powerful, capable analytics on your infrastructure and resources across hybrid and multi-cloud environments.
  • Splunk Application Performance Monitoring (APM) Splunk APM collects and analyzes every span and trace from each of the services that you have connected to Splunk Observability Cloud to give you full-fidelity access to all of your application data.
  • Splunk Real User Monitoring (RUM) Provides insights about the performance and health of the front-end user experience of your application.
  • Splunk Synthetic Monitoring Synthetically measures the performance of your web-based properties and offers features that provide insights that enable you to optimize uptime and performance of APIs, service endpoints, and end-user experiences and prevent web performance issues.
  • Splunk Log Observer Allows you to perform codeless queries on logs and troubleshoot your application and infrastructure behavior using high-context logs to detect the source of problems in your systems.
  • Splunk On-Call Splunk On-Call incident response software aligns log management, monitoring, chat tools, and more, for a single pane of glass into system health.
  • Splunk Observability Cloud for Mobile Splunk Observability Cloud for Mobile is an iOS and Android companion mobile app to Splunk Observability Cloud.

Whether you need full-fidelity monitoring and troubleshooting for applications, infrastructure, or users, Splunk provides it all in real-time and at any scale. Splunk supports integration with Amazon CloudWatch, Google Cloud Platform, Microsoft Azure, Docker, Kafka, Kubernetes, and more. This allows you to get data from your on-premises and cloud infrastructure, applications and services, and user interfaces into Observability Cloud. A free 14-day-trial of Splunk Observability Cloud with full access to all the features is available on request.

Datadog vs Splunk: How They Compare

Installation and Set Up

Datadog is a SaaS-based application, there are no on-premise system requirements and no installation hassles. However, you’ll be required to install local agents specific to the device or service you wish to monitor for the most part. An agent-based mode means no auto-discovery feature, so you have to deploy an agent for all your devices individually. Datadog supports integration with VMware vSphere, but the setup process is a bit complicated. That said, Datagod provides enough documentation and setup instructions to guide you through the installation and configuration process.

On the other hand, Splunk offers both SaaS-based and self-hosted versions. The SaaS-based version needs no installation other than an internet-connected device with a supported browser. Once you create a plan, set up your organization, and get data into Observability Cloud, you can then explore and analyze them. If you choose the self-hosted version known as Splunk Enterprise, you need to install it on your Windows or Linux server. Once the installation is completed, you can add your applications and infrastructure. Self-hosted platforms give you granular control over the system, but you also have to manage it yourself.

Dashboards and Visualizations

Datadog dashboards are generally more user-friendly and aesthetically pleasing from a visual perspective with their clean and modern dashboard design. In addition, Datadog allows you to customize your dashboards with a vast library of visualization tools and drag-and-drop widgets. But it requires a lot of setup work to get things working. Once set up, there are two primary ways of visualizing your data:

  1. Screenboards These are grid-based dashboards with free-form layouts that include images, tables, host maps, graphs, and logs. They are commonly used as status boards or storytelling views that update in real-time or represent fixed points in the past.
  2. Timeboards This represents a single point in time—fixed or real-time—across the entire dashboard. They are commonly used for troubleshooting, correlation, and general data exploration. In addition, you also get a time series that can plot any metric being captured from your hosts, such as CPU usage, uptime, or memory usage.

Splunk Observability Cloud provides custom, built-in, and user dashboards and dashboard groups that you can use to understand your data. Custom dashboards require some work to customize and get things working. Unlike custom dashboards, built-in dashboard groups behave like templates and are automatically created for you and give immediate visibility into your environment. Your user dashboard group is your workspace within Observability Cloud. Once the dashboards are set up, users and admins can view charts, gain better visibility, and make sense of complex data and critical events happening in your environment.

Alerts and Notifications

Datadog’s approach to alerts and notifications is based on machine learning (ML), which it calls Watchdog. Watchdog uses ML techniques to identify problems in your infrastructure, applications efficiency and services, and flag anomalies. Alerts in Datadog are called Monitors. Users can receive alerts using Pagerduty, Slack, and email. These can be based on nearly any metric that Datadog can capture. As a result, every alert is specific, actionable, and contextual—even in large and temporary environments. This unique approach to alerts and notifications makes Datadog stand out and helps to minimize downtime and prevents alert fatigue.

Splunk Observability Cloud uses detectors, events, alerts, and notifications to keep you informed when certain criteria are met. The Splunk alerting system is designed to elicit a response in a timely fashion and accelerate issue resolution. Alerts inform network admins about faults or anomalies and trigger actions such as email or slack notifications. Splunk alert can also be configured to send notifications via a webhook, or Splunk On-Call—a powerful incident response tool that extends the alerting and messaging, and allows you to centralize the flow of information throughout the incident lifecycle. Splunk comes with built-in alerting conditions that detect common problem scenarios, and provide more powerful ways of monitoring signals than the standard practice of comparing a signal to a static threshold.

Reporting and Integration

Instead of generating the usual out-of-the-box reports that most network admins expect, Datadog’s approach to reporting aims to make metrics easily searchable, and it does excellently. Although some network managers prefer reports to be generated in good old PDF format, not everybody needs it in that format these days. Therefore, Datadog also comes equipped with an easy-to-use API that can significantly extend the range of what Datadog can track. The Datadog API is an HTTP REST API that can access the Datadog platform programmatically and returns JSON from all requests. Similarly, Datadog’s ability to support and integrate with more than 500 technologies makes it more versatile and adapted to many different functions than Splunk.

Splunk allows you to create and edit reports, including the ability to manually create a report on Splunk Web. Once you create a report you can view the results that the report returns on the report viewing page. You can also schedule reports to perform actions each time they run, such as sending report results via email to key stakeholders. Splunk integrates with a little over 100 technologies. This is much less when compared to Datadog which supports far more than that. But it doesn’t matter as long as Splunk meets your integration requirements. Nevertheless, Splunk supports a wide range of data formats, like.xml, .csv and .json files. Those with needs that require such data stream integration from multiple data formats should opt for Splunk, as Datadog offers little support in this regard.

Licensing and Price Plans

Datadog pricing model is based on per server, per month, and it’s free for up to 5 hosts (with 1-day data retention). But some customers complain that it becomes costly at scale. As a result, Datadog is available in several different pricing tiers:

  • The Network Performance tier – suitable for monitoring networks and systems for most small to midsize businesses.
  • The Infrastructure tier – ideal for organizations that want to use the software as a centralized monitoring service for systems and services.
  • The APM tier – designed for larger organizations looking to fix service and device-layer problems.
  • Serverless tier – aimed at those looking to monitor network and application issues.
  • Log Management tier – meant for companies with large amounts of log data to parse for context and retention.
  • There are also other security, synthetic, and accurate user monitoring, each appropriate pricing for the core task.

All Datadog prices are billed annually, making it one of the most price-customizable management apps.

The Splunk Cloud Platform pricing model is based on Workload Pricing measured with Splunk Virtual Compute units (SVCs) and Ingest Pricing measured in GB/day for select deployments. Under the Workload Pricing model, Splunk offers license allocation based on compute capacity. SVC is a unit of cloud computing, memory and I/O resources. Workload pricing is a value-oriented pricing option that can help align your Splunk investment with your search activity and provide the flexibility to bring data volume without ingesting limits.

The traditional ingest-based pricing model is based purely on your data volume requirements. The total plan price is determined by multiplying your desired daily index volume by the unit price per GB. All plan prices include support such as software updates and customer support.

Target marketIdeal solution for medium to large-scale enterprises.Developers, freelancers, IT operations teams, security engineers, and business users from SMBs to large organizations in the cloud age.
Security capabilitiesAnalytics-driven SIEM, and security orchestration, automation and response (SOAR) solution.Cloud SIEM, workload security,
application Security monitoring, and more
Deployment modelCloud, self-hostedCloud
Integration 100+500+
Data formatsProvides support for multiple types of data formats like.xml, .csv and .json files.Does not support multiple types of data formats.
Support methodsPhone
Online case submission
Knowledge Base
Knowledge base
Video tutorials
Licensing and pricing modelFree trial available
Pricing model is based on computing capacity, or data volume requirements measured in GB/day
Free trial available
Pricing model is based on per server, per month

Table 1.0 | Comparison of Splunk and Datadog key features

Choosing Between Datadog and Splunk

Datadog and Splunk have both distinguished themselves in the observability and security monitoring space. Deciding between the duo shouldn’t be about which is better, but about the one that best meets your performance and security monitoring needs.

Datadog’s SaaS-based model makes it ideal for organizations that don’t want to burden themselves with any resource-intensive on-premise monitoring solution. Service-oriented companies, SMBs, or smaller networks that don’t have dedicated IT personnel to keep tabs on the infrastructure at a granular level will find this feature-rich tool suitable. More extensive networks with multiple remote locations may find Datadog’s agent-based model inconvenient since agents will need to be individually installed. But if you can successfully get past the agent installation and configuration process, Datadog is a mature and excellent network observability platform.

Splunk’s flexible deployment model makes it ideal for organizations that want to be in complete control, but it comes at the cost of a skilled human resource.  Nonetheless, organizations seeking all-encompassing observability and security monitoring capabilities will find Splunk closer to their needs. Splunk’s feature-rich solution offerings cover a large amount of ground if you have the financial muscle required to grab it. If your organization is a large enterprise with minimal integration requirements no more than offered, and would rather be billed based on compute capacity or data volume requirements; then Splunk is your best bet.