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Cribl vs Datadog comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Jul 13, 2025

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

ROI

Sentiment score
3.5
Cribl is cost-effective compared to Splunk, but not all users see clear returns in time and cost savings.
Sentiment score
7.0
Datadog enhances visibility, reduces downtime, saves costs, and optimizes workflows by integrating features and improving operational efficiency.
 

Customer Service

Sentiment score
5.3
Cribl's customer support is effective and prompt, with high satisfaction despite some noted areas needing improved understanding of customer needs.
Sentiment score
7.1
Datadog's customer service is responsive and knowledgeable, though some users report delays with complex queries and phone support.
They had extensive expertise with the product and were able to facilitate everything we needed.
The community, including the engineering and sales teams, is available on Slack and is very supportive.
 

Scalability Issues

Sentiment score
5.5
Cribl is highly scalable, enabling efficient workload distribution and quick deployment, appealing to businesses of all sizes.
Sentiment score
7.6
Datadog efficiently scales with cloud services, offering seamless expansion, though users highlight the importance of monitoring pricing.
I don't need to talk to a Cribl engineer to connect a new log source.
Cribl is quite scalable, as we could add worker nodes as our data grows.
It is pretty scalable, just in terms of cost.
 

Stability Issues

Sentiment score
5.8
Cribl is stable and reliable, with quick bug resolution and improvements over time despite occasional connectivity issues.
Sentiment score
8.0
Datadog offers reliable and stable performance with minimal downtime, impressive uptime, and efficient monitoring, even during peak periods.
In deploying it into enterprise or production environments, it's quite reliable.
If the pipeline is down and we receive an alert that it's not sending information to the log collection platform for more than one or two hours, if we receive an alert, it would be great.
 

Room For Improvement

Cribl faces compatibility issues, UI limitations, and documentation inconsistencies, requiring enhancements in integration, customization, and data handling.
Datadog needs improved performance, interface simplification, clearer billing, better integration, customization, analytics, documentation, security, and mobile app integration.
In terms of large datasets—whether they originated from network inputs, virtual machines, or cloud instances—ingesting the data into the destination was relatively easy.
Perhaps more flexibility in terms of metrics would be helpful.
In future updates, I would like to see AI features included in Datadog for monitoring AI spend and usage to make the product more versatile and appealing for the customer.
The documentation is adequate, but team members coming into a project could benefit from more guided, interactive tutorials, ideally leveraging real-world data.
There should be a clearer view of the expenses.
 

Setup Cost

Cribl offers competitive pricing valued for cost-effectiveness and scalability, though its complex credit system can cause confusion.
Datadog offers flexible pricing based on usage and organization size, with potential for high costs if not monitored closely.
I don't think any other solution offers this much value at this price point.
The setup cost for Datadog is more than $100.
 

Valuable Features

Cribl provides efficient, real-time data transformation and routing, supporting scalability, cost reduction, and rapid integration for enhanced operational efficiency.
Datadog offers intuitive, comprehensive monitoring and integrations, enhancing infrastructure and application management with real-time insights and efficient operations.
The data reduction and preprocessing capabilities make Cribl really unique.
The community on Slack is excellent for solving questions and getting ideas.
Our architecture is written in several languages, and one area where Datadog particularly shines is in providing first-class support for a multitude of programming languages.
The technology itself is generally very useful.
 

Categories and Ranking

Cribl
Ranking in Application Performance Monitoring (APM) and Observability
13th
Ranking in Log Management
7th
Average Rating
8.4
Reviews Sentiment
6.3
Number of Reviews
16
Ranking in other categories
Security Information and Event Management (SIEM) (10th), Observability Pipeline Software (1st)
Datadog
Ranking in Application Performance Monitoring (APM) and Observability
1st
Ranking in Log Management
3rd
Average Rating
8.6
Reviews Sentiment
7.1
Number of Reviews
188
Ranking in other categories
Network Monitoring Software (4th), IT Infrastructure Monitoring (2nd), Container Monitoring (1st), Cloud Monitoring Software (2nd), AIOps (1st), Cloud Security Posture Management (CSPM) (7th)
 

Mindshare comparison

As of September 2025, in the Application Performance Monitoring (APM) and Observability category, the mindshare of Cribl is 1.0%, up from 0.2% compared to the previous year. The mindshare of Datadog is 7.2%, down from 10.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Application Performance Monitoring (APM) and Observability Market Share Distribution
ProductMarket Share (%)
Datadog7.2%
Cribl1.0%
Other91.8%
Application Performance Monitoring (APM) and Observability
 

Featured Reviews

Abdullah Zubair - PeerSpot reviewer
Enables seamless SIEM/Data Migration and Log Filtration across the enterprise estate
They've already done many good things with the product, but perhaps they could implement a temporary SIEM solution where we could store logs and display them as a SIEM, though I think that's not the space that Cribl is actually looking into. Based on my experience, this product is brilliant and there isn't much or anything important lacking in the product. We encountered some occasional issues with the syslog data stream, particularly when handling large data volume, and getting it to parse and field extracted correctly, but no major alarms that would halt the days operation. There were few source vendor specific challenges, but overall, I didn't notice anything major beyond that. Most of the process went smoothly. However, we did need to carry some troubleshooting to resolve the issues we faced while connecting with other platforms and few data stream miss-behaving, which wasn't a straightforward task for us. In terms of large datasets—whether they originated from network inputs, virtual machines, or cloud instances—ingesting the data into the destination was relatively easy. In summary, aside from the usual difficulties or issues that someone could face with any project, everything else went well.
reviewer820579 - PeerSpot reviewer
Single pane of glass, easy to share dashboards, and good for monitoring
We've had some issues where we had Datadog automatically turned on in AWS regions that we weren't using, which incurred a small but steady cost that amounted to tens of thousands of dollars spent over a few weeks. I wish there was a global setting that lets an admin restrict which regions DD is turned on in as a default setup step. Sometimes, the APM service dashboard link isn't sharable. I click something in the service catalog, and on that service's APM default view, I try to share a link to that with a teammate, and they reach a blank or error screen. I wish there was more organization and detail in the suggestions when I use the query editor. I'm never quite sure when the autofill dropdown shows up if I'm seeing some custom tag or some default property, so I have to know exactly what I'm looking for in order to build a chart. It's hard to navigate and explore using the query autofill suggestions without knowing exactly what tag to look for. It's been a bit hard to understand how data gets sampled or how many data points a particular dashboard value is using. We've had questions over the RUM metrics that we see and we had to ask for help with how values are calculated, bin sizes, etc to get confidence in our data.
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Top Industries

By visitors reading reviews
Financial Services Firm
16%
Computer Software Company
9%
Manufacturing Company
7%
Healthcare Company
7%
Financial Services Firm
14%
Computer Software Company
14%
Manufacturing Company
8%
Healthcare Company
5%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business8
Midsize Enterprise4
Large Enterprise6
By reviewers
Company SizeCount
Small Business78
Midsize Enterprise42
Large Enterprise82
 

Questions from the Community

What is your experience regarding pricing and costs for Cribl?
I think the pricing for Cribl is reasonable. For large usage, but I heard the calculation of those credits is a bit complicated.
What needs improvement with Cribl?
So since we’re handling a ton of data, I think we could really benefit from a more integrated or connected way to manage it all. Like, if there is a way to better track data lineage, metadata, thos...
What is your primary use case for Cribl?
We use Cribl Stream to collect logs from multiple sources, transform and enrich them, filter out unnecessary data before sending them to SIEM. We also use Cribl to route logging to data lake.
Any advice about APM solutions?
There are many factors and we know little about your requirements (size of org, technology stack, management systems, the scope of implementation). Our goal was to consolidate APM and infra monitor...
Datadog vs ELK: which one is good in terms of performance, cost and efficiency?
With Datadog, we have near-live visibility across our entire platform. We have seen APM metrics impacted several times lately using the dashboards we have created with Datadog; they are very good c...
Which would you choose - Datadog or Dynatrace?
Our organization ran comparison tests to determine whether the Datadog or Dynatrace network monitoring software was the better fit for us. We decided to go with Dynatrace. Dynatrace offers network ...
 

Comparisons

 

Overview

 

Sample Customers

Information Not Available
Adobe, Samsung, facebook, HP Cloud Services, Electronic Arts, salesforce, Stanford University, CiTRIX, Chef, zendesk, Hearst Magazines, Spotify, mercardo libre, Slashdot, Ziff Davis, PBS, MLS, The Motley Fool, Politico, Barneby's
Find out what your peers are saying about Cribl vs. Datadog and other solutions. Updated: September 2025.
867,349 professionals have used our research since 2012.