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.
"Datadog is providing efficiency in the products we develop for the wireless device engineering department."
"The integration into AWS is key as well as our software is currently bound to AWS."
"The dashboards and the performance of the software have been great."
"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."
"I have found the logging and tracing features the most valuable."
"Datadog agents act as an integration to different services, providing easy access and management."
"We really like the charts and visualization."
"APM and tracing are super useful."
"The most valuable feature is the machine learning capability."
"The most valuable feature of Elastic Security is that you can install agents, and they are not separately licensed."
"The most valuable feature is the ability to collect authentication information from service providers."
"The most valuable feature is the scalability. We are in Indonesia, more engineers understand Elastic Security here. So it is easier to scale and also develop. In features, the discovery to query all the logs is very important to us. It is very easy, especially with the query function and the feature to generate alerts and create tools. Sometimes we use the alert security dashboard to monitor our clients."
"Enables monitoring of application performance and the ability to predict behaviors."
"The solution has a good community surrounding it for lots of helpful documentation for troubleshooting purposes."
"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."
"It is an extremely stable solution. Stability-wise, I rate the solution a ten out of ten."
"Datadog is so feature-rich that it is often hard to onboard new folks and tough to decide where to invest time."
"The setup was a bit complex."
"Sometimes, it takes a long time to load the dashboard if we have many charts."
"The incident management beta looks promising, but it is still missing the ability to automatically create incidents based on certain alerts."
"The documentation could be improved regarding setting up the agent properly and debugging."
"When I started using it years ago, it had stability problems. I remember, specifically, we ran everything in Docker containers. There were some problems getting it into a Docker container with very specific memory limits."
"Ingesting data from various sources to monitor the log metrics of the system can always improve so that, if something goes wrong, the right teams are alerted."
"Alerting timing should be improved to be more fine-tuned and exact."
"If the documentation were improved and made more clear for beginners, or even professionals, then we would be more attracted to this solution."
"Technical support could respond faster."
"Elastic Security has a steep learning curve, so it takes some time to tune it and set it up for your environment. There are some costs associated with logging things that don't have value. So you need to be cautious to only log things that make sense and keep them around for as long as you need. You shouldn't hold onto things just because you think you might need them."
"The interface could be more user friendly because it is sometimes hard to deal with."
"Better integration with third-party APMs would be really good."
"Their visuals and graphs need to be better."
"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."
"This type of monitoring is not very mature just yet. We need more real-time information in a way that's easier to manage."
Datadog is ranked 2nd in Log Management with 137 reviews while Elastic Security is ranked 5th in Log Management with 58 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 AppDynamics, whereas Elastic Security is most compared with Wazuh, Splunk Enterprise Security, Microsoft Sentinel, Microsoft Defender for Endpoint and IBM Security QRadar. 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?