

Datadog and Elastic Observability are major players in the comprehensive monitoring solutions category. Datadog seems to have the upper hand due to its extensive integrations and intuitive interface, making it particularly suited for cloud-native environments.
Features:Datadog offers a robust hosted service with valuable features like sharable dashboards, TimeBoards, and extensive API integrations including dogstatsd and Slack. Its intuitive tagging system facilitates actionable visualizations essential for cloud-native environments. Elastic Observability stands out with its powerful text search capabilities and seamless integration across various environments, offering open-source flexibility for extensive customization.
Room for Improvement:Datadog could enhance user experience by improving interface intuitiveness, expanding real-time usage analytics, and increasing integration options. Cost control and better support for front-end applications are also noted areas for improvement. Elastic Observability could focus on improving ease of use, providing more detailed metrics, and enhancing its visualization tools. Expanding AI-driven insights would benefit both.
Ease of Deployment and Customer Service:Datadog provides flexible deployment across various cloud environments, appealing to large enterprises with hybrid setups. Its customer service is highly regarded for being responsive, although some users suggest it could be faster. Elastic Observability is praised for its consistent high-quality customer service, with real-time chat support as a major advantage. Users report a positive experience but cite a need for more in-depth technical solutions.
Pricing and ROI:Datadog is noted for its comprehensive features, although it can be costly, particularly when scaling up in larger infrastructures. Its usage-based pricing model can lead to unexpected costs without diligent oversight. Elastic Observability is often seen as more cost-effective for large-scale deployments, offering predictable pricing options. Both solutions provide significant ROI, but Elastic Observability's straightforward pricing model is appealing for budget-conscious users.
Previously we had thirteen contractors doing the monitoring for us, which is now reduced to only five.
Datadog has delivered more than its value through reduced downtime, faster recovery, and infrastructure optimization.
We have also seen fewer escalations for minor issues because alerts help us catch problems earlier, which indirectly reduces downtime and improves overall efficiency.
Elastic Observability has saved us time as it's much easier to find relevant pieces across the system in one screen compared to our own software, and it has saved resources too since the same resources can use less time.
When I have additional questions, the ticket is updated with actual recommendations or suggestions pointing me in the correct direction.
Overall, the entire Datadog comprehensive experience of support, onboarding, getting everything in there, and having a good line of feedback has been exceptional.
I've had a couple instances where I reached out to Datadog's support team, and they have been really super helpful and very kind, even reaching back out after resolving my issues to check if everything's going well.
Elastic support really struggles in complex situations to resolve issues.
Their excellent documentation typically helps me solve any issues I encounter.
Datadog's scalability has been great as it has been able to grow with our needs.
Since it is a SaaS platform, we did not have to worry about backend scaling.
We have not faced any major performance issues from the platform side; it handles increased metrics and monitoring loads smoothly.
I rate the scalability of Elastic Observability as a ten, as we have never seen issues even with a lot of data coming in from more customers, provided we have the appropriate configuration.
Elastic Observability seems to have a good scale-out capability.
Elastic Observability is easy in deployment in general for small scale, but when you deploy it at a really large scale, the complexity comes with the customizations.
Metrics collection and alerting have been consistent in day-to-day use.
Datadog is very stable, as there hasn't been any downtime or issues since I've been here, and it's always on time.
Datadog seems stable in my experience without any downtime or reliability issues.
There are some bugs that come with each release, but they are keen always to build major versions and minor versions on time, including the CVE vulnerabilities to fix it.
I would rate the stability of Elastic Observability as a ten, as we don't experience any issues.
Elastic Observability is really stable.
It would be great to see stronger AI-driven anomaly detection and predictive analytics to help identify potential issues before they impact performance.
We want to be able to customize the cost part, and we would appreciate more granular access control.
Having more transparent and granular cost control features would make it easier to manage usage.
For instance, if you have many error logs and want to create a rule with a custom query, such as triggering an alert for five errors in the last hour, all you need to do is open the AI bot, type this question, and it generates an Elastic query for you to use in your alert rules.
It lacked some capabilities when handling on-prem devices, like network observability, package flow analysis, and device performance data on the infrastructure side.
Some areas such as AI Ops still require data scientists to understand machine learning and AI, and it doesn't have a quick win with no-brainer use cases.
The setup cost for Datadog is more than $100.
Pricing is mainly based on data ingestion, such as logs, metrics, and traces, and it can increase quickly if everything is enabled by default.
Everybody wants the agent installed, but we only have so many dollars to spread across, so it's been difficult for me to prioritize who will benefit from Datadog at this time.
Elastic Observability is cost-efficient and provides all features in the enterprise license without asset-based licensing.
Observability is actually cheaper compared to logs because you're not indexing huge blobs of text and trying to parse those.
Many customers struggle to understand their total cost of ownership because Elastic licensing is not dependent on easy, quantifiable metrics such as number of users or amount of data.
Our architecture is written in several languages, and one area where Datadog particularly shines is in providing first-class support for a multitude of programming languages.
Having all that associated analytics helps me in troubleshooting by not having to bounce around to other tools, which saves me a lot of time.
Datadog was able to find the alerts and trigger to notify our team in a very prompt manner before it got worse, allowing us to promptly adjust and remediate the situation in time.
The most valuable feature is the integrated platform that allows customers to start from observability and expand into other areas like security, EDR solutions, etc.
the most valued feature of Elastic is its log analytics capabilities.
Every integration, whether for Windows or Linux or even Palo Alto or Fortinet, installs the out-of-the-box dashboards along with it, making it easy to parse incoming data meaningfully and immediately start viewing dashboards to see what's happening in the platform.
| Product | Mindshare (%) |
|---|---|
| Datadog | 4.1% |
| Elastic Observability | 1.5% |
| Other | 94.4% |


| Company Size | Count |
|---|---|
| Small Business | 81 |
| Midsize Enterprise | 50 |
| Large Enterprise | 100 |
| Company Size | Count |
|---|---|
| Small Business | 9 |
| Midsize Enterprise | 4 |
| Large Enterprise | 16 |
Datadog offers a comprehensive platform for monitoring applications and infrastructure, providing insights into real-time metrics and optimizing performance with extensive integrations and analytics capabilities.
Datadog provides a robust monitoring platform designed for applications and infrastructure tracking. With intuitive dashboards and real-time metrics visibility, it enhances operational efficiency and enables proactive incident management. The platform supports data centralization across services, reducing downtime through its monitoring capabilities. Integration with AWS, Kubernetes, and other systems aligns with performance tracking and infrastructure management, while APM and RUM features allow tracing and user behavior analytics.
What are Datadog's Key Features?Industries utilizing Datadog benefit from detailed monitoring and comprehensive analytics across multi-cloud environments. Companies in e-commerce, finance, and technology sectors implement it for end-to-end monitoring ensuring robust application performance. The platform assists in maintaining standards through integration with services like AWS and Azure, providing efficient observability and allowing proactive issue resolution.
Elastic Observability is known for its powerful search capabilities, central logging, and integration with cloud-native tasks. It enhances monitoring for applications and systems through its flexibility and machine learning features.
Elastic Observability is a robust tool offering end-to-end monitoring and performance analysis, widely utilized for application performance monitoring, centralized logging, and metrics collection. Kibana enables data visualization and connection of sources, while the platform aids in incident response with real-time insights. Despite its complex learning curve, limited customization, and licensing challenges, it remains valuable for businesses seeking to improve operational efficiency with additional support from log analytics and system automation.
What are the key features of Elastic Observability?A wide range of industries apply Elastic Observability for its capabilities in capturing significant data points to offer insights into business and technical performance. Its applications span log events, application monitoring, network protocol monitoring, and more, aiding in data-driven decision-making processes within sectors like IT, finance, and e-commerce.
We monitor all Application Performance Monitoring (APM) and Observability reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.