Datadog and Splunk are enterprise analytics, monitoring, and security software solutions that both offer infrastructure monitoring tools. Here, we’ll compare them based on their respective infrastructure monitoring capabilities.
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Datadog vs. Splunk: Core features
A strong foundation of core features is essential when selecting a data analytics solution, as it directly impacts the value and insights that can be derived from your data. In the showdown between Datadog and Splunk, both contenders boast a robust set of features, but with distinct areas of focus.
Datadog is renowned for its comprehensive infrastructure and application performance monitoring (APM) capabilities. By providing real-time insights into your applications, services, and infrastructure, Datadog enables you to proactively address performance issues and optimize resource utilization. One of the standout features of Datadog is its distributed tracing functionality, which helps developers pinpoint bottlenecks and optimize application performance. Furthermore, the platform’s machine learning-powered anomaly detection and alerting system ensures that you’re always in the know when it comes to performance deviations, allowing for swift remediation of issues.
Splunk excels in the realm of log management and analysis. With its powerful search, correlation, and visualization capabilities, Splunk turns raw log data into actionable insights. The software’s signature feature, the Search Processing Language (SPL), empowers users to create complex queries and conduct in-depth analysis of their data. Beyond log analysis, Splunk has expanded its offerings to include security information and event management (SIEM) with its Splunk Enterprise Security (ES) solution, making it a valuable tool for organizations looking to strengthen their security posture. Additionally, Splunk’s IT Service Intelligence (ITSI) module provides a holistic view of your IT environment, helping to identify and prioritize issues before they impact your business.
Datadog shines when it comes to infrastructure and application monitoring, offering a wealth of features that cater to modern, cloud-native environments. Meanwhile, Splunk stands out as a powerful log analysis and security solution, delivering granular insights and comprehensive visibility into your data. When evaluating the core features of these two software giants, consider which aspects are most relevant to your organization’s needs and priorities.
Datadog vs. Splunk: Ease of use
When it comes to monitoring and managing data, the user experience can make all the difference. In the high-stakes world of data analytics, a software solution that is easy to use can empower your team to work more efficiently and make more informed decisions. In the battle between Datadog and Splunk, ease of use is a key factor to consider.
Datadog has built a reputation for its user-friendly interface and intuitive dashboards. Its drag-and-drop functionality simplifies the creation of custom visualizations and alerts, making it easy for even non-technical users to get started. A standout feature of Datadog is the extensive library of pre-built integrations, which streamlines the process of connecting various data sources and services. With over 400 integrations available, Datadog offers a seamless onboarding experience, enabling your team to hit the ground running.
Splunk’s interface is often described as more complex and powerful, catering to a user base with more advanced technical skills. Splunk’s Search Processing Language (SPL) allows users to dive deep into data analysis and create custom queries that reveal hidden insights. While this level of customization can be a major advantage for experienced users, it may also present a steeper learning curve for newcomers. That being said, Splunk has made strides in recent years to improve the user experience with features like the Data Model Acceleration and Guided Data Onboarding, which simplify data ingestion and visualization.
Datadog vs. Splunk: Integrations
Both vendors claim comprehensive tech stack visibility, however, there is one clear forerunner in this regard. With Datadog, administrators have complete visibility across the tech stack with over 500 built-in integrations that aggregate metrics and events across the tech stack, including SaaS and cloud providers, databases, and more.
Splunk, in contrast, includes more than 250 out-of-the-box integrations. Since Datadog has at least double the integration capabilities as Splunk, it’s imperative to double check which apps and services need to be connected to the monitoring tool of choice and whether those plug-ins are compatible with the vendor of choice.
Datadog vs. Splunk: Metrics tracking
Metrics tracking allows data engineers to set parameters for measuring infrastructure performance.
With Datadog IT engineers decide which metrics to index that are valuable for a query. Your queries can extend beyond metrics directly related to IT. With DogStatsD, you can include business-level custom metrics, such as revenue or customer behavior, as well.
Once metrics are decided, they’re not set in stone; you can go back and change them any time. It’s also easy to preserve the mathematical accuracy and granularity of the queries you set up. With Datadog, you can track tens of thousands of infrastructure metrics out-of-the-box and view continuous historical records, even on infrastructure that doesn’t exist anymore.
Datadog vs. Splunk: Dashboards
Datadog’s out-of-the-box dashboards allow you to analyze data from across your entire tech ecosystem on one page. Users can use templates and auto-generated dashboards without knowledge of coding or a query language, making it user friendly for data visualization purposes. If you want a more hands-on approach, you can create customized dashboards using Datadog’s library of visualization tools and drag-and-drop widgets.
Splunk offers dashboards templates to monitor your entire stack. Once the dashboard is set up, users can autodiscover, breakdown, group, and explore clouds, services, systems, availability systems, Kubernetes clusters, and more. It’s unclear whether users need to know code or a query language to use this feature, so it may not be as user friendly as Datadog.
Datadog vs. Splunk: Troubleshooting
When something goes wrong, you want a monitoring solution that will alert you as quickly as possible to tech stack problems and, even better, proactively identify and address issues.
With Datadog’s tool, users can troubleshoot quickly with one-click correlation of related metrics, traces, and logs from across the stack. This enables the user to pinpoint issues and see how they affect other elements of the infrastructure.
Splunk’s real-time streaming analytics enables quick alerts to issues. Its AI-driven troubleshooting enables Splunk to proactively find and flag issues and to predict on dynamic thresholds, multiple conditions, and complex rules, thereby reducing the mean amount of time to repair (MTTR). Given Splunk’s AI-powered troubleshooting that allows for proactive glitch redress, Splunk wins in terms of troubleshooting.
Datadog vs. Splunk: Key differences
While both Datadog and Splunk’s product suites focus on security and monitoring/observability, Datadog offers a wider range of individual tools allowing for an á la carte-style product selection, unless one opts for its security platform. Splunk bundles similar tools together and offers two different types of platforms (Splunk Cloud and Splunk Enterprise). Below is a table of shared and unique tools between Datadog and Splunk:
Also read on eWeek: Datadog vs. Splunk 2022 Software Comparison
Choosing Datadog vs. Splunk
Users prefer Datadog overall for its frequent product updates and for its ease of use and implementation. Datadog also appears to be more established in the infrastructure monitoring space, since it has significantly more reviews than Splunk’s tool does. Datadog offers a wide range of individual tools to choose from, making it a great option if your organization already has security and/or monitoring software but could use enhancements.
Splunk, on the other hand, offers smaller product bundles and two platform options, which is what you need if your company lacks sufficient security and observability or your current system needs a complete overhaul.
If you’re having trouble deciding if Datadog or Slunk are right for you, our Technology Advisors are here to help out. They can help you narrow your search to the right network monitoring or IT software for your requirements. Use the Security Software Buyer’s Guide to get your short list of vendors today.
1. What are the main differences between Datadog and Splunk?
Datadog primarily focuses on infrastructure and application performance monitoring, providing real-time insights into applications, services, and infrastructure. Splunk excels in log management and analysis, offering powerful search and correlation capabilities for raw log data. Additionally, Splunk has expanded its scope to include security information and event management (SIEM) and IT service intelligence.
2. Is Datadog easier to use than Splunk?
Datadog is generally considered more user-friendly, with an intuitive interface and a vast library of pre-built integrations, making it easier for non-technical users to get started. Splunk has a more complex interface that caters to users with advanced technical skills, although recent updates have improved its overall user experience.
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