We performed a comparison between Datadog and Elastic Observability based on our users’ reviews in five categories. After reading all of the collected data, you can find our conclusion below.
Features: Datadog offers a range of valuable features, such as customizable dashboards and detailed reporting. It also excels in error reporting and log centralization, making it easier to identify and address issues. The platform's ease of use and simple setup process are appreciated by users. Performance monitoring and infrastructure monitoring are reliable, and the platform offers flexibility and additional features. Elastic Observability is known for its cost-effectiveness and favorable licensing. The comprehensive features and easy deployment and flexibility are key strengths, and the platform's machine learning capabilities are appreciated. Elastic Observability offers stable performance and has a well-designed interface. Datadog could enhance its usability, integration, learning curve, external website monitoring, and SSL security. Elastic Observability, meanwhile, requires improvements in auto-discovery, visualization, metrics, and role-based access control.
Service and Support: Some users have found the support provided by Datadog to be helpful and responsive, while others have experienced slow or unresponsive support. Elastic Observability's customer service has been highly praised for its excellent technical support and quick responses. Some customers even have a dedicated resource for their issues.
Ease of Deployment: Users generally findDatadog's initial setup to be simple and uncomplicated, with support readily accessible. The setup process for Elastic Observability varies in difficulty. While it is deemed straightforward for Docker installation, some users encounter difficulties due to various cluster configurations and distributed solutions.
Pricing: Datadog's setup cost is mixed in terms of its affordability. The pricing model is unclear and lacks documentation. Elastic Observability provides various pricing options, including a self-managed license with three tiers. It incorporates embedded or open-source components, potentially making it more economical.
ROI: Users have reported various benefits from using Datadog, including time savings and faster debugging. Elastic Observability has been found to be cost-effective, helping to reduce incidents and identify issues effectively.
Comparison Results: Elastic Observability is praised for its cost-effectiveness, favorable licensing, comprehensive features, easy deployment, and customization flexibility. Users highly value its machine learning capabilities and stable performance, making it the preferred solution.
"The fact that everything is under a single pane of glass is really valuable, as developers don't have to spend their time copying correlation IDs across tools to find what they need."
"It has a nice UI."
"We enjoy the multistep API tests."
"The most valuable features of Datadog are the flexibility and additional features when compared to other solutions, such as AppDynamics and Dynatrace. Some of the features include AI and ML capabilities and cloud and analysis monitoring"
"The observability pipelines are the most valuable aspect of the solution."
"Having a wealth of information has helped us investigate outages, and having historical data helps us tune our system."
"Datadog provides tracing and logging, whereas Dynatrace focuses on tracing, and Splunk is more of a logging tool. Datadog's advantage is that we don't need two tools."
"We integrate our application logs. It is great to be able to tie our metrics and our traces together."
"Its diverse set of features available on the cloud is of significant importance."
"I have built a mini business intelligence system based on Elastic Observability."
"The most valuable feature of Elastic Observability is the text search."
"Elastic APM has plenty of features, such as the Elastic server for Kibana and many additional plugins. It's a comprehensive tool when used as a logging platform."
"We use AppDynamics and Elastic. The reason why we're using Elastic APM is because of the license count. It's very favorable compared to AppDynamics. It's inexpensive; it's economical."
"The Elastic User Interface framework lets us do custom development when needed. You need to have some Javascript knowledge. We need that knowledge to develop new custom tests."
"It's easy to deploy, and it's very flexible."
"The solution is open-source and helps with back-end logging. It is also easy to handle."
"At times, it can be hard to generate metrics out of logs."
"We would like to see smaller or shorter tutorials and video sessions."
"The solution needs to integrate AI tools."
"I want to applaud the efforts in making the UI extremely usable and approachable. My suggestion would be to take another look at how the menu structure is put together, however. Even after using the platform mostly every day for months, I still find myself trying to find a service or feature in the menus."
"The sheer amount of products that are included can be overwhelming."
"Geo-data is also something very critical that we hope to see in the future."
"I've found that the documentation is lacking in certain regards."
"The menu on the left is pretty dense (and I know it has to be). I never knew about the cmd+k functionality until recently. It would be helpful to offer more tips/cheat sheets to see handy shortcuts like that."
"Improving code insight related to infrastructure and network, particularly focusing on aspects such as firewalls, switches, routers, and testing would be beneficial."
"There is room for improvement regarding its APM capabilities."
"The solution needs to use more AI. Once the product onboards AI, users would more effectively be able to track endpoints for specific messages."
"Elastic Observability needs to have better standardization, logging, and schema."
"More web features could be added to the product."
"There could be more low-code features included in the product."
"The interface could be improved."
"Elastic Observability’s price could be improved."
Datadog is ranked 1st in Application Performance Monitoring (APM) and Observability with 137 reviews while Elastic Observability is ranked 7th in Application Performance Monitoring (APM) and Observability with 22 reviews. Datadog is rated 8.6, while Elastic Observability is rated 7.8. The top reviewer of Datadog writes "Very good RUM, synthetics, and infrastructure host maps". On the other hand, the top reviewer of Elastic Observability writes "The user interface framework lets us do custom development when needed. ". Datadog is most compared with Dynatrace, Azure Monitor, New Relic, AWS X-Ray and AppDynamics, whereas Elastic Observability is most compared with Dynatrace, New Relic, AppDynamics, Azure Monitor and Grafana. See our Datadog vs. Elastic Observability report.
See our list of best Application Performance Monitoring (APM) and Observability vendors, best IT Infrastructure Monitoring vendors, and best Log Management vendors.
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.