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 most valuable feature I have found is the elastic container service."
"I have found the logging and tracing features the most valuable."
"I have found error reporting and log centralization the most valuable features. Overall, Datadog provides a full package solution."
"Since we integrated Datadog, we have had increased confidence in the quality of our service, and we had an easier time increasing our delivery velocity."
"The solution has helped our organization with custom events to track specific cases."
"The biggest thing I liked was the combination of all the things - monitoring, log aggregation, and profiling."
"Datadog's log aggregation is really helpful since it lets me and every other engineer on my team login, view, and share logs when we need to debug our application."
"We find they have a very helpful alert system."
"Machine learning is the most valuable feature of this solution."
"I have built a mini business intelligence system based on Elastic Observability."
"The solution is open-source and helps with back-end logging. It is also easy to handle."
"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."
"Elastic Observability significantly improves incident response time by providing quick access to logs and data across various sources. For instance, searching for specific keywords in logs spanning over a month from multiple data sources can be completed within seconds."
"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 solution allows us to dig deep into data."
"This service could be less costly."
"Managing dashboards as IaC is a bit hard to work out at times."
"The installation is easy for me. However, if you are new to this solution it might not be so easy."
"They need to implement template variables into the message response body."
"The correlation between the logs and the metrics needs improvement as most cases, we might use another logging tool (that is cheaper in cost) which we then have to link together."
"There is always room for improvement when dealing with cloud-based technologies. Mainly, I would say, it's just increasing our offerings to attract various other types of industries and businesses across more fields."
"Datadog could improve the flexibility with AI and ML concepts. This will allow customers to be more leveraged towards publishing."
"I often have issues with the UI in my browser."
"Elastic APM's visualization is not that great compared to other tools. It's number of metrics is very low."
"The interface could be improved."
"The solution needs to use more AI. Once the product onboards AI, users would more effectively be able to track endpoints for specific messages."
"Improving code insight related to infrastructure and network, particularly focusing on aspects such as firewalls, switches, routers, and testing would be beneficial."
"They need more skills in the market. There are not enough skills in the market. It is not pervasive enough on the market, in my opinion. In other words, there isn't a big enough user base."
"There could be more low-code features included in the product."
"In the future, Elastic APM needs a portfolio iTool. They can provide an easy way to develop the custom UI for Kibana."
"There is room for improvement regarding its APM capabilities."
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.