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's seamless integration with Slack and PagerDuty helped us to receive alerts right to the most common notification methods we use (our mobile devices and Slack)."
"The integration into AWS is key as well as our software is currently bound to AWS."
"Datadog's ability to group and visualize the servers and the data makes it relatively easy for the root cause analysis."
"The platform appeals to companies spanning many industries on a global scale."
"We really like the charts and visualization."
"We've found it most useful for managing Rstudio Workbench, which has its own logs that would not be picked up via Cloudwatch."
"It is easy to implement and scale applications with standardized visibility, monitoring and alerting"
"Having a clear view, not only of our infrastructure but our apps and services as well, has brought a great added value to our customers."
"What customers found most valuable in Elastic Security feature-wise is the search capability, in particular, the way of writing the search query and the speed of searching for results."
"The indexes allow you to get your results quickly. The filtering and log passing is the advantage of Logstash."
"We've found the initial setup to be quite straightforward."
"Stability-wise, I rate the solution a ten out of ten."
"The most valuable features are the speed, detail, and visualization. It has the latest standards."
"It is an extremely stable solution. Stability-wise, I rate the solution a ten out of ten."
"I like that it's a SIEM platform. I like that I can sell Elastic Security quickly. Elastic Security has a large community that can support users."
"It can handle millions of loads at a time, and you can always use the filters to find exactly what you are looking for and detect errors in every log message you are searching for, basically."
"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 error traceability is an area that can be improved."
"The dashboard could be improved. It would be helpful to get a view of specific things that we need to monitor for our application."
"It would be nice to be able to graph metrics by excluding certain tags (like you can do in monitors)."
"The logging could be improved in the future."
"Datadog is so feature-rich that it is often hard to onboard new folks and tough to decide where to invest time."
"Datadog lacks a deeper application-level insight. Their competitors had eclipsed them in offering ET functionality that was important to us. That's why we stopped using it and switched to New Relic. Datadog's price is also high."
"The incident management beta looks promising, but it is still missing the ability to automatically create incidents based on certain alerts."
"This type of monitoring is not very mature just yet. We need more real-time information in a way that's easier to manage."
"Its documentation should be a bit better. I have to spend at least a couple of hours to find the solution for a simple thing. When we buy Elastic, training is not included for free with Elastic. We have to pay extra for the training. They should include training in the price."
"One thing they could add is a quick step to enable users who don't have a solid background to build a dashboard and quickly search, without difficulty."
"The solution's query building is not that intuitive compared to other solutions."
"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."
"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."
"The price of this product could be improved, especially the additional costs. I would also like to see better-quality graphics."
"They don't provide user authentication and authorisation features (Shield) as a part of their open-source version."
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.
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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?