Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Datadog
Score 8.7 out of 10
N/A
Datadog is a monitoring service for IT, Dev and Ops teams who write and run applications at scale, and want to turn the massive amounts of data produced by their apps, tools and services into actionable insight.
$18
per month per host
Kibana
Score 8.2 out of 10
N/A
Kibana allows users to visualize Elasticsearch data and navigate the Elastic Stack so you can do anything from tracking query load to understanding the way requests flow through your apps.N/A
Pricing
DatadogKibana
Editions & Modules
Log Management
$1.27
per month (billed annually) per host
Infrastructure
$15.00
per month (billed annually) per host
Standard
$18
per month per host
Enterprise
$27
per month per host
DevSecOps Pro
$27
per month per host
APM
$31.00
per month (billed annually) per host
DevSecOps Enterprise
$41
per month per host
No answers on this topic
Offerings
Pricing Offerings
DatadogKibana
Free Trial
YesNo
Free/Freemium Version
YesNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeOptionalNo setup fee
Additional DetailsDiscount available for annual pricing. Multi-Year/Volume discounts available (500+ hosts/mo).
More Pricing Information
Community Pulse
DatadogKibana
Considered Both Products
Datadog
Chose Datadog
Kibana
Datadog
… because within our usecase we have all the events in Kibana but sampled traces in Datadog … but if we had all the traces it would have been much more useful
Chose Datadog
All other tools dont have all the features which Datadog provides.
Easy to use from UI where other may have complicated UI or no UI at all to create monitors. Consider like AWS Grafana, we have limitation to create monitors from UI. There is no recurring downtime for monitors. …
Kibana
Chose Kibana
Well when it comes to using Kibana when compared to Datadog, I can say that Kibana is pretty [...] cheap. Apart from APM and Datadog hosted agents, Kibana gives a good competition to Datadog for real time log analysis as well as metrics analysis.
While OpsGenie is a great tool …
Features
DatadogKibana
BI Standard Reporting
Comparison of BI Standard Reporting features of Product A and Product B
Datadog
-
Ratings
Kibana
7.1
5 Ratings
13% below category average
Pixel Perfect reports00 Ratings6.02 Ratings
Customizable dashboards00 Ratings8.15 Ratings
Report Formatting Templates00 Ratings7.23 Ratings
Ad-hoc Reporting
Comparison of Ad-hoc Reporting features of Product A and Product B
Datadog
-
Ratings
Kibana
6.6
5 Ratings
17% below category average
Drill-down analysis00 Ratings7.95 Ratings
Formatting capabilities00 Ratings7.04 Ratings
Integration with R or other statistical packages00 Ratings5.01 Ratings
Report sharing and collaboration00 Ratings6.64 Ratings
Report Output and Scheduling
Comparison of Report Output and Scheduling features of Product A and Product B
Datadog
-
Ratings
Kibana
6.8
2 Ratings
19% below category average
Publish to Web00 Ratings8.02 Ratings
Publish to PDF00 Ratings8.02 Ratings
Report Versioning00 Ratings6.02 Ratings
Report Delivery Scheduling00 Ratings6.02 Ratings
Delivery to Remote Servers00 Ratings6.02 Ratings
Data Discovery and Visualization
Comparison of Data Discovery and Visualization features of Product A and Product B
Datadog
-
Ratings
Kibana
6.7
4 Ratings
14% below category average
Pre-built visualization formats (heatmaps, scatter plots etc.)00 Ratings7.94 Ratings
Location Analytics / Geographic Visualization00 Ratings7.02 Ratings
Predictive Analytics00 Ratings6.02 Ratings
Pattern Recognition and Data Mining00 Ratings6.01 Ratings
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DatadogKibana
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Sumo Logic
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Score 9.3 out of 10
Supermetrics
Supermetrics
Score 9.9 out of 10
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NetBrain Technologies
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All AlternativesView all alternativesView all alternatives
User Ratings
DatadogKibana
Likelihood to Recommend
9.4
(55 ratings)
7.9
(5 ratings)
Usability
9.2
(34 ratings)
8.0
(1 ratings)
Support Rating
8.9
(6 ratings)
7.7
(2 ratings)
User Testimonials
DatadogKibana
Likelihood to Recommend
Datadog
Datadog may be better suited for teams that have a more out-of-the-box infrastructure, on the primary platforms Datadog supports. You may also have better results if you have a bigger team dedicated to devops and/or a bigger budget. We found that trying to adapt it to our use case (small team, .NET on AWS Fargate) wasn't feasible. We continually ran into roadblocks that required us to dig through documentation (and at times, having to figure out some documentation was wrong), go back and forth with support, and in my opinion, waste money on excessive and unintended usages due to opaque pricing models and inaccurate usage reports, as well as broken/non-functional rate sampling controls.
Read full review
Elastic
Kibana is indeed a powerful tool and has many use cases especially in environments that rely heavily on real-time log analysis and visualisation. Kibana’s ability to handle large volumes of log data and present it in an accessible, searchable format is invaluable. We use Kibana to monitor security related issues and it proactively alerts our Slack channels about any anomality or issues.
Read full review
Pros
Datadog
  • The thing which Datadog does really well, one of them are its broad range of services integrations and features which makes it one step observability solution for all. We can monitor all types of our application, infrastructure, hosts, databases etc with Datadog.
  • Its custom dashboard feature which helps us to visualize the data in a better way . It supports different types of charts through those charts we can create our dashboard more attractive.
  • Its AI powered alerting capability though that we can easily identify the root cause and also it has a low noise alerting capability which means it correlated the similar type of issues.
Read full review
Elastic
  • Fast searches with powerful index.
  • Beautiful data visualizations.
  • Real-time observability.
Read full review
Cons
Datadog
  • Alert windows cause lag in notifications (e.g. if the alert window is X errors in 1 hour, we won't get alerted until the end of the 1 hour range)
  • I would appreciate more supportive examples for how to filter and view metrics in the explorer
  • I would like a more clear interface for metrics that are missing in a time frame, rather than only showing tags/etc. for metrics that were collected within the currently viewed time frame
Read full review
Elastic
  • Some performance issues with large datasets.
  • Linking to dashboards makes extremely long urls.
  • Lack of reports.
Read full review
Likelihood to Renew
Datadog
Definitely will not revisit after our issues and, in my opinion, poor support.
Read full review
Elastic
No answers on this topic
Usability
Datadog
There are so many features that it can be hard to figure out where you need to go for your own use case. For example, RUM monitoring us buried in a "Digital Experience" sidebar setting when this is one of our key use cases that I sometimes struggle to find in the application. It appears that ECS + Fargate monitoring was recently released which is great because we had to build a lambda reporting solution for ephemeral task monitoring. But this new feature was never on my radar until I starting clicking around the application.
Read full review
Elastic
Its usability is generally good and it provides teams with a basic to intermediate understanding about data visualization. It is very user-friendly when it comes to creating dashboards. The UI is very good and simple. Its integration with other tools for alerting and reporting is amazing. But its advance features have a learning curve and a first timer needs some time to use the advance features.
Read full review
Support Rating
Datadog
The support team usually gets it right. We did have a rather complicate issue setting up monitoring on a domain controller. However, they are usually responsive and helpful over chat. The downside would be I don’t think they have any phone support. If that is important to you this might not be a good fit.
Read full review
Elastic
We did not use the official Kibana support. Documentation was easy enough to follow.
Read full review
Implementation Rating
Datadog
Documentation was difficult to work through, rollout was catastrophic (completely outage)
Read full review
Elastic
No answers on this topic
Alternatives Considered
Datadog
Our logs are very important, and Datadog manages them exceptionally well. We frequently use Datadog services for our investigations. Use case: Monitor your apps, infrastructure, APIs, and user experience.


Key features:


Logs, metrics, and APM (Application Performance Monitoring)


Real-time alerting and dashboards


Supports Kubernetes, AWS, GCP, and other integrations


RUM (Real User Monitoring) and Synthetics





✅ Best for backend, server, and distributed systems monitoring.
Read full review
Elastic
Kibana is free; it was the first and only thing we've tried in this area.
Read full review
Return on Investment
Datadog
  • Saved us (time & money) from developing our own monitoring utilities that would pale in comparison
  • Alerts allow us to remedy issues before our customers even know about them
  • Tracking resource usage over time allows us to better plan for future needs, before it becomes a pain-point.
Read full review
Elastic
  • Issues that affect checkout experiences for customers are able to be prioritized and solved quickly.
  • We are able to more efficiently use resources due to the automation of reporting alerts. Decreasing employee resources needed.
  • Visualization allows us to quickly share issues and explain to coworkers in order to escalate issues that can cost our bottom line.
Read full review
ScreenShots

Datadog Screenshots

Screenshot of the out-of-the-box and customizable monitoring dashboards.Screenshot of Datadog's collaboration features, where users can discuss issues in-context with production data, annotate changes and notify their teams, see who responded to that alert before, and discover what was done to fix it.Screenshot of where Datadog unifies traces, metrics, and logs—the three pillars of observability.Screenshot of some of Datadog's 400+ built-in integrations.Screenshot of Datadog's Service Map, which decomposes an application into all its component services and draws the observed dependencies between these services in real timeScreenshot of centralized log data, pulled from any source.