Cribl Stream is a vendor-agnostic observability pipeline used to collect, reduce, enrich, normalize, and route data from any source to any destination within an existing data infrastructure. It is used to achieve full control of an organization's data stream.
N/A
Datadog
Score 8.8 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
Pricing
Cribl Stream
Datadog
Editions & Modules
No answers on this topic
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
Offerings
Pricing Offerings
Cribl Stream
Datadog
Free Trial
No
Yes
Free/Freemium Version
No
Yes
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
Optional
Additional Details
—
Discount available for annual pricing. Multi-Year/Volume discounts available (500+ hosts/mo).
Advantages - if you'd like to re-shape/manipulate data, Cribl LogStream comes to help! - If you'd like to enrich data within data pipeline without any struggle, Cribl LogStream is the one! - If you'd like to reduce data size, cribl is the one! Disadvantages - there is ML/AI module for streaming data. - There is no sigma integration for security use cases.
Datadog can be pricey for larger scale businesses, so it really depends on your use case. For us, we have a small single deployment application and a small developer team, so our costs are mostly reasonable. There are more features than we can explore which can be somewhat overwhelming. It is mostly easy and intuitive to use but for larger scale you may consider rolling your own solutions.
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.
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
There is some room for improvement, but the Datadog team sends out updates frequently, and the UI is user-friendly for engineers, with no significant loading issues or region-specific problems. That was one of the key reasons we preferred Datadog; our company has employees worldwide, and it wasn't difficult to transition to the tool.
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.
-Cribl LogStream has a huge growing community and plugin play packs that help you to onboard and reduce your size within 5 min. -Friendly user interface -The broker feature saves your life against regulations. - field extraction's never been so easy before. - multiple sources and destinations feature to give you an easy playground.
It's a one-stop solution for all our needs whereas in other open-source tools, we have an operational overhead to keep and manage the uptime of these tools as well and also manage their versioning, upgrade, and patching cycle. Also if there are any bugs then we have to raise an open source issue and many problems as we have to keep 2 to 3 people aligned to manage the stack.
