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.
"We can handle debugging and find out why things are breaking in our applications."
"APM is great and has provided low-effort out-of-the-box observability for various services."
"The most useful feature is the APM."
"Integrating Datadog with other platforms has made our monitoring processes a bit easier. It's not super simple, but it's manageable."
"Their interface is probably one of the easiest things to use because it lets non-developers and non-engineers quickly get access to metrics and pull business value out of them. We could put together dashboards and give it to people who are non-technical, then they can see the state of the world."
"I don't have to worry about upgrades with the AWS version."
"Sometimes it's more user friendly for development teams. There are some parts of Datadog that are more understandable for development teams. For example, the APM in Datadog works more manually and works like the tools in New Relic or Grafana, or Elastic. It is easier to understand for software development teams."
"The observability on offer is the most useful aspect of the product."
"ELK documentation is very good, so never needed to contact technical support."
"The solution is compatible with the cloud-native environment and they can adapt to it faster."
"We've found the initial setup to be quite straightforward."
"It's very customizable, which is quite helpful."
"The most valuable feature is the machine learning capability."
"The feature that we have found the most valuable is scalability."
"The most valuable features of the solution are the prevention methods and the incident alerts."
"The indexes allow you to get your results quickly. The filtering and log passing is the advantage of Logstash."
"Billing should be more transparent."
"It would be great if usage metrics were automatically created and we could create custom metrics, instead we ended up building some of our own stuff to track and alert on our own usage."
"Datadog could always lower the price!"
"Once Datadog has gained wide adoption, it can often be overwhelming to both know and understand where to go to find answers to questions."
"It can be overwhelming for new people as it has a lot of features."
"I would love to see more metrics or analytics in IoT devices."
"The solution should provide alerts for cloud outages."
"Datadog could be improved if it could detect other software in a container or server."
"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."
"Anything that supports high availability or ease of deployment in a highly available environment would help to improve this solution."
"The solution needs to be more reactive to investigations. We need to be able to detect and prevent any attacks before it can damage our infrastructure. Currently, this solution doesn't offer that."
"There are connectors to gather logs for Windows PCs and Linux PCs, but if we have to get the logs from Syslog then we have to do it manually, and this should be automated."
"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."
"I think because we are a cybersecurity company, the thing that can be improved is the prebuilt tools, especially quality. Compared to its competitor, they still have fewer prebuilt security rules. Elastic Security, in terms of generating alerts, cannot group the same products into one another. Even though the alerts are the same, they still generate them one by one. So, it is very noisy in our dashboard. I would like the Elastic Security admin to group all the same alarms into one alarm so that our dashboard is not noisy."
"Better integration with third-party APMs would be really good."
"We'd like to see some more artificial intelligence capabilities."
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?