We performed a comparison between Datadog and Elastic Security (formerly ELK Logstash) based on our users’ reviews in five categories. After reading all of the collected data, you can find our conclusion below.
Comparison Results: Datadog and Elastic Security have a similar user rating for ease of deployment, and users of both felt that the solutions were expensive. Users felt Elastic Security took too long to respond when it came to service and support. In terms of features, reviewers of Datadog had a problem with stability and felt there wasn’t enough monitoring through their dashboard. Reviewers of Elastic Security said they had difficulty retrieving data and felt the solution should offer predictive maintenance.
"They have a very good foundation in capturing metrics, logs, and traces. It's a very nice tool for that and it allows you to apply these monitoring tools in almost any technology."
"The platform appeals to companies spanning many industries on a global scale."
"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."
"Thanks to the logs, we manage to make better reports through Jira and also to trace the request with more facility than we would be able to do otherwise."
"If we have a large load for users using our basic Datadog, it will immediately fire off an alert notifying us either something's wrong or not."
"With Datadog I can look at the health of the technology stack and services."
"We can handle debugging and find out why things are breaking in our applications."
"The RUM solution has improved our ability to triage faster and hand more capabilities to our customer support."
"It's very customizable, which is quite helpful."
"We've found the initial setup to be quite straightforward."
"The most valuable thing is that this solution is widely used for work management and research. It's easy to jump into the security use case with the same technology."
"Just the ability to do a lot more than just up-down is nice, which a lot of people take for granted."
"The cost is reasonable. It's not overly pricey."
"The most valuable features are the speed, detail, and visualization. It has the latest standards."
"Elastic is straightforward, easy to integrate, and highly customizable."
"We like Elastic Security because it's a REST API-based solution. That's the primary reason we use it."
"We need more advanced querying against logs."
"The pricing model could be simplified as it feels a bit outdated, especially when you look at the billing model of compute instances vs the containers instances."
"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."
"Datadog could always lower the price!"
"I've found that the documentation is lacking in certain regards."
"The current way accounts are billed could be vastly improved - especially when involving multiple organizations across multiple accounts in combination with reserved commitments."
"The logging could be improved in the future."
"I would love to see more metrics or analytics in IoT devices."
"We had issues with scalability. Logstash was not scaling and aggregation was getting delayed. We moved to Fluentd making our stack from ELK to EFK."
"Elastic has one problem. In the past, Elastic Security was free. Now, they currently only offer the basic license or a certain period of time."
"The tool should improve its scalability."
"The solution could also use better dashboards. They need to be more graphical, more matrix-like."
"Improvements in Elastic Security could include refining and normalizing queries to make them more user-friendly, enhancing the user experience with better documentation, and addressing any latency issues."
"Technical support could respond faster."
"They don't provide user authentication and authorisation features (Shield) as a part of their open-source version."
"It's a little bit of a learning curve to understand the logic of searching for things and trying to find what you're looking for in Elastic Security."
Datadog is ranked 3rd in Log Management with 137 reviews while Elastic Security is ranked 5th in Log Management with 59 reviews. Datadog is rated 8.6, while Elastic Security is rated 7.6. The top reviewer of Datadog writes "Very good RUM, synthetics, and infrastructure host maps". On the other hand, the top reviewer of Elastic Security writes "A stable and scalable tool that provides visibility along with the consolidation of logs to its users". Datadog is most compared with Dynatrace, Azure Monitor, New Relic, AWS X-Ray and Elastic Observability, whereas Elastic Security is most compared with Wazuh, Splunk Enterprise Security, Microsoft Sentinel, IBM Security QRadar and Microsoft Defender for Endpoint. See our Datadog vs. Elastic Security report.
See our list of best Log Management vendors.
We monitor all Log Management 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.
It depends on your requirement. If you are looking for a SIEM/log management solution ELK would be a better option.
But if you are looking for more of a monitoring solution Datadog would be better. Also, Datadog provides out-of-the-box integrations with a lot of cloud applications. ELK could be cost-effective but a bit challenging to configure & finetune.
Datadog: Unify logs, metrics, and traces from across your distributed infrastructure. Datadog is the leading service for cloud-scale monitoring. It is used by IT, operations, and development teams who build and operate applications that run on dynamic or hybrid cloud infrastructure. Start monitoring in minutes with Datadog!
Datadog features offered are:
200+ turn-key integrations for data aggregation
Clean graphs of StatsD and other integrations
Elasticsearch: Open Source, Distributed, RESTful Search Engine. Elasticsearch is a distributed, RESTful search and analytics engine capable of storing data and searching it in near real time. Elasticsearch, Kibana, Beats and Logstash are the Elastic Stack (sometimes called the ELK Stack).
Elasticsearch provides the following key features:
Distributed and Highly Available Search Engine.
Multi Tenant with Multi Types.
Various set of APIs including RESTful
Dear,
Unfortunately, I can't say much about Datadog but I have used ELK for a short period.
And I can tell you not everything works the way it should. For example, I noticed heavy CPU usage for a Windows client on MS AD servers. I advise you to consider this if it's important to you.
Good luck!
Where do you want to spend your money, on people or licenses?
ELK requires a long-term investment in engineering resources to manage the system and to provide the capability.
Datadog provides capabilities for you so you only need some administrators. What are the capabilities? Some critical ones include availability, scalability, consuming log files, platform upgrades, ...
If you are consuming smaller data sets (100's of GB) with shorter retention, the size and scaling are much easier making ELK easier.
Do you have admins or engineers? If your team doesn't have dedicated time & skills to spend developing solutions like elastic-alert you should look for a vendor to provide capabilities.
I expect some capabilities in Datadog you will not be able to replicate in ELK.... so that answer makes this obvious.
We are going to evaluate the same for our org. We do about 10 TB a day consumption in ELK and are looking to see if we can shift $$$ from engineers and infra to SaaS.
I have used both ELK and Datadog, and there are lots of variables to consider here. The three important points that I looked at are:
- Cost. In addition to service costs, you have to consider egress and ingress costs as well.
- Real-time observability that you need during development vs long-term Observability. Keep in mind, when you export data over the internet, it comes with the same reliability issues as any other service on the internet. Regardless of how Datadog classifies its service as real-time, it is not real-time, IMO. It very much depends on your definition of real-time.
- Deployment and maintenance complexity. When your ELK cluster grows it has some pain points you need to be aware of.
My general approach is to deploy ELK for development, tune the data, and then pivot toward commercial solutions if I need to. This gives you insight into your data and what you should be preserving and that way you are not paying high costs, when or if you do decide to take advantage of a commercial solution.
Can you tell me what you actually want to do so that I can help you?