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 ingestion points are unlimited and support customization. We haven't had anything yet that we haven't been able to integrate with it."
"Datadog has a lot of features to be able to drill down deep into the swath of logs that our platforms generate."
"It is easy to navigate the menu and create tests."
"The many dozens of integrations that the solution brings out of the box are excellent."
"It has enhanced the performance of my team."
"Most of the features in the way Datadog does monitoring are commendable and that is the reason we choose it. We did some comparisons before picking Datadog. Datadog was recommended based on the features provided."
"It has turned into an operational dashboard. If you felt something is going wrong, you can immediately open up Datadog. It has been our go to application because we know the answer will be there."
"The installation step is pretty straightforward."
"It's easy to deploy, and it's very flexible."
"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."
"The solution is open-source and helps with back-end logging. It is also easy to handle."
"The solution allows us to dig deep into data."
"The product has connectors to many services."
"Good design and easy to use once implemented."
"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."
"The solution has been stable in our usage."
"One area where I was really looking for improvement was the CSPM product line. I had really wanted to have team-level visibility for findings, since the team managing the resources has much more context and ability to resolve the issue, as the service owner. However, this has been added to the announcement in a recent keynote."
"Datadog is expensive."
"The current way accounts are billed could be vastly improved - especially when involving multiple organizations across multiple accounts in combination with reserved commitments."
"They should continue expanding and integrating with more third-party apps."
"We need more advanced querying against logs."
"Its pricing model can be improved. Its settings should be improved for a better understanding of billing. They should also provide some alerts when there is an increase in the usage. For example, if there is 20% more increase from one week to another, the customer should get an alert."
"The more tools that they can build that allow you to run AWX playbooks, or other similar fixes, would benefit clients greatly."
"When it comes to storing the logs with Datadog, I'm not sure why it costs so much to store gigabytes or terabytes of information when it's a fraction of the cost to do so myself."
"The price is the only issue in the solution. It can be made better and cheaper."
"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 is reactive rather than proactive. It should act as an ITSM tool and be able to create tickets and alerts on Jira."
"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."
"Elastic Observability needs to improve the retrieval of logs and metrics from all the instances."
"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 Sentry. 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.
