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.
"Excellent autocomplete for everything in the UI."
"With Datadog I can look at the health of the technology stack and services."
"We integrate our application logs. It is great to be able to tie our metrics and our traces together."
"We have been able to set very specific CPU and memory alerts, at the very base level, then we started to pull real business value, like 99th percentile response rates for our API calls."
"We've found it most useful for managing Rstudio Workbench, which has its own logs that would not be picked up via Cloudwatch."
"I don't have to worry about upgrades with the AWS version."
"I like that you can build out a dashboard pretty quickly. There are some things that come out of the box that you don't really need to do, which is great because they're default settings."
"The monitoring functionality, in general, and tagging infrastructure are great."
"The most valuable feature is the search function, which allows me to go directly to the target to see the specific line a customer is searching for."
"I can look at events from more than one source across multiple different locations and find patterns or anomalies. The machine learning capabilities are helpful, and I can create rules for notifications to be more proactive rather than responding after something has gone wrong."
"Elastic has a lot of beats, such as Winlogbeat and Filebeat. Beats are the agents that have to be installed on the terminals to send the data. When we install beats or Elastic agents on every terminal, they don't overload the terminals. In other SIEM solutions such as Splunk or QRadar, when beats or agents are installed on endpoints, they are very heavy for the terminals. They consume a lot of power of the terminals, whereas Elastic agents hardly consume any power and don't overload the terminals."
"It's a good platform and the very best in the current market. We looked at the Forester report from December 2022 where it was said to be a leader."
"Elastic Security is a highly flexible platform that can be implemented anywhere."
"It's not very complicated to install Elastic."
"The most valuable features of Elastic Security are it is open-source and provides a high level of security."
"We chose the product based on the ability to scan for malware using a malware behavioral model as opposed to just a traditional hash-based antivirus. Therefore, it's not as intensive."
"It can have an artificial intelligence component. Even though I can seamlessly look at end-to-end security, it would be better to have alerts and notifications powered by an AI engine. I am not sure if they have an AI component. We have not reached out to them or looked at it, but this is something that I keep on talking about within our company in terms of features. Such a feature would be good to have, and it would further optimize my Security Ops team's abilities."
"The on-premise version is very difficult to upgrade."
"We need more visibility into the error tracking dashboard."
"We need more integration with security tools like Drata."
"There is occasional UI slowness and bugs."
"Datadog needs more local Asia-Pacific support, and if they don't have a SaaS solution in Asia-Pacific, they should offer an on-prem version. I'm told that's not possible."
"We have contact with many customers that cover many areas, so we have cases where the infrastructure administration could be improved."
"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."
"This type of monitoring is not very mature just yet. We need more real-time information in a way that's easier to manage."
"If you compare this with CrowdStrike or Carbon Black, they can improve."
"We're using the open-source edition, for now, I think maybe they can allow their OLED plugin to be open source, as at the moment it is commercialised."
"The biggest challenge has been related to the implementation."
"The price of this product could be improved, especially the additional costs. I would also like to see better-quality graphics."
"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."
"The solution does not have a UI and this is one of the reasons we are looking for another solution."
"I would like more ways to manage permissions and restrict access to certain users."
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?