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 solution is useful for monitoring logs."
"The solution has helped our organization with custom events to track specific cases."
"The ease with which we can filter, use metrics, and give accounts to customers, then let the customer filter, set up metrics, and alerts. This has been a big win for us."
"Datadog has made it much easier to have a central place for people to look for logs and made it much easier to notify them of any elevated error rates or failures."
"Datadog has a lot of features to be able to drill down deep into the swath of logs that our platforms generate."
"Datadog is providing efficiency in the products we develop for the wireless device engineering department."
"The solution has helped out organization gain improved visibility."
"Its integration definitely stands out. It provides seamless monitoring of all our systems, services, apps, and whatever else we secure and monitor. Visualizations have become simpler with dashboards. We are getting visibility into systems, services, and apps stack through a single pane of glass, which is good. We are able to put logs in context."
"Good design and easy to use once implemented."
"For full stack observability, Elastic is the best tool compared with any other tool ."
"The price is very less expensive compared to the other solutions."
"Its diverse set of features available on the cloud is of significant importance."
"It is a powerful tool that allows users to collect and transform logs as needed, enabling flexible visualization and analysis."
"The ability to ensure that the data is searchable and maintainable is highly valuable for our purposes."
"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."
"I have built a mini business intelligence system based on Elastic Observability."
"Lacks some flexibility in the customization."
"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."
"Since the Datadog platform has so many separate features, solving so many use cases, there are often inconsistencies in feature availability and interoperability between products."
"Datadog needs more local Asia-Pacific support, and if they don't have a SaaS solution in Asia-Pacific, they should offer an on-prem version. I'm told that's not possible."
"Datadog isn't as mature as some of the established players like Dynatrace or Splunk. It's a new product, so they are constantly releasing new features, and I don't have much to complain about."
"I would love to see more metrics or analytics in IoT devices."
"We need to learn more about the session reply feature inside of DD."
"This service could be less costly."
"The price is the only issue in the solution. It can be made better and cheaper."
"Elastic Observability’s price could be improved."
"The tool's scalability involves a more complex implementation process. It requires careful calculations to determine the number of nodes needed, the specifications of each node, and the configuration of hot, warm, and cold zones for data storage. Additionally, managing log retention policies adds further complexity. The solution's pricing also needs to be cheaper."
"Improving code insight related to infrastructure and network, particularly focusing on aspects such as firewalls, switches, routers, and testing would be beneficial."
"More web features could be added to the product."
"Elastic Observability is reactive rather than proactive. It should act as an ITSM tool and be able to create tickets and alerts on Jira."
"Elastic Observability needs to have better standardization, logging, and schema."
"Elastic Observability is difficult to use. There are only three options for customization but this can be difficult for our use case. We do not have other options to choose the metrics shown, such as CPU or memory usage."
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 Splunk Enterprise Security, whereas Elastic Observability is most compared with Dynatrace, New Relic, AppDynamics, Sentry 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.
