

Grafana and Cribl compete in the data management and analytics category. Cribl seems to have the upper hand due to its focus on efficient data handling and cost reduction, coupled with a wide array of data processing features.
Features: Grafana is renowned for its data visualization capabilities, offering customizable dashboards and extensive integration options for seamless integration with various data sources. Cribl specializes in real-time data processing, log management, and simplified data transformation, ensuring flexibility and cost efficiency in handling vast data volumes.
Room for Improvement: Grafana could benefit from enhanced security features, better reporting, and a more user-friendly interface. It also requires improvement in documentation and the installation process. Cribl could improve its documentation, integration with legacy systems, and versioning systems, alongside better logging and alerting capabilities.
Ease of Deployment and Customer Service: Grafana offers flexible deployment options on-premises and in the public cloud, with robust community support crucial for open-source users. Cribl supports on-premises and hybrid cloud deployments, ensuring excellent customer service although its deployment experience could be enhanced through better documentation.
Pricing and ROI: Grafana provides a cost-effective solution with a free open-source version and budget-friendly enterprise options. Cribl offers competitive pricing, especially when compared to platforms like Splunk, delivering substantial value for money and generating significant cost savings with its data ingestion strategies.
What we've seen is really an overall reduction of just shy of 40% in our ingest into our SIM platform versus prior to having Cribl.
The second thing is that data aggregation, sampling, and reduction that we're able to do of the data, lowering our overall data volume, both traversing the network as well as what's being stored inside of our final solutions.
In terms of reduction, we were able to save almost ~40% of our total cost.
I identified over-provisioned servers and reduced my AWS monthly bill by 15%, which is a significant saving in terms of costs.
They had extensive expertise with the product and were able to facilitate everything we needed.
Usually, within an hour, we get a response, and we are able to work with them back and forth until we resolve the issues.
Sometimes by hearing the problem itself, they will know what the solution is, and they will let us know how to resolve it, and we do it immediately.
The technical support team is very helpful with complex PromQL troubleshooting.
My advice for people who are new to Grafana or considering it is to reach out to the community mainly, as that's the primary benefit of Grafana.
I do not use Grafana's support for technical issues because I have found solutions on Stack Overflow and ChatGPT helps me as well.
The infrastructure behind Cribl Search is also scalable as it uses a CPU and just spawns horizontally more instances as it demands and requires.
Compared to other SIEM tools I use, any slight change on the operating system end impacts a lot on our SIEM tools and other things, but Cribl performs well in that regard.
It's an enterprise version, and we have a good amount of users using this solution.
It is highly scalable and built on a big data architecture capable of ingesting trillions of data points.
In terms of our company, the infrastructure is using two availability zones in AWS.
In assessing Grafana's scalability, we started noticing logs missing or metrics not syncing in time.
Migrating from those SC4S servers to Cribl worker nodes has truly been a game-changer.
Regarding scalability, we started with zero servers and have around 285 servers now.
I would rate the stability as ten out of ten.
When something in their dashboard does not work, because it is open source, I am able to find all the relative combinations that people are having, making it much easier for me to fix.
Once you get to a higher load, you need to re-evaluate your architecture and put that into account.
Even when handling millions of data points, the visualization layer remains responsive.
A more stringent role-based access control feature would enhance security and allow granular control over what users can see and access.
If we can have more internal logs and more debug logs to validate the error, that would be beneficial because instead of reaching out to Cribl support, we can troubleshoot and find the root cause ourselves.
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.
It would be better if they made the technology easy to use without needing to read extensive documentation.
Grafana cannot be easily embedded into certain applications and offers limited customization options for graphs.
I would want to see improvements, especially in the tracing part, where following different requests between different services could be more powerful.
Over time, the licensing cost has increased.
Cribl is very inexpensive, with enterprise pricing around 30 cents per GB, which is really decent.
They have a universal license that allows us to consume the portions of Cribl that we want to use or flex into other portions of Cribl.
In an enterprise setting, pricing is reasonable, as many customers use it.
The costs associated with using Grafana are somewhere in the ten thousands because we are able to control the logs in a more efficient way to reduce it.
I purchased my Grafana Cloud subscription through the AWS Marketplace, which simplified my procurement process and allowed me to apply the cost towards my AWS committed spend.
The data reduction and preprocessing capabilities make Cribl really unique.
Cribl has a feature called JSON Unroll or Unroll function that allows you to differentiate the events; each event will come ingested as a single log instead of piling it up with multiple events.
The Cribl UI is very simple and easy to use, particularly when working with data from various sources; it makes it very easy to create pipelines, add complex logic to those pipelines, and then gives you a preview of what your data looks like before applying that pipeline and what you get after.
Users can monitor metrics with greater ease, and the tool aids in quickly identifying issues by providing a visual representation of data.
The fact that I can join data from my SQL database with metrics from Prometheus in the same table is a feature I have not found performed as well elsewhere.
Its alerting feature is effective because it allows me to set thresholds to send an email if a certain threshold is met.
| Product | Market Share (%) |
|---|---|
| Grafana | 3.6% |
| Cribl | 1.2% |
| Other | 95.2% |


| Company Size | Count |
|---|---|
| Small Business | 9 |
| Midsize Enterprise | 5 |
| Large Enterprise | 18 |
| Company Size | Count |
|---|---|
| Small Business | 13 |
| Midsize Enterprise | 8 |
| Large Enterprise | 25 |
Cribl offers advanced data transformation and routing with features such as data reduction, plugin configurations, and log collection within a user-friendly framework supporting various deployments, significantly reducing data volumes and costs.
Cribl is designed to streamline data management, offering real-time data transformation and efficient log management. It supports seamless SIEM migration, enabling organizations to optimize costs associated with platforms like Splunk through data trimming. The capability to handle multiple data destinations and compression eases log control. With flexibility across on-prem, cloud, or hybrid environments, Cribl provides an adaptable interface that facilitates quick data model replication. While it significantly reduces data volumes, enhancing overall efficiency, there are areas for improvement, including compatibility with legacy systems and integration with enterprise products. Organizations can enhance their operational capabilities through certification opportunities and explore added functionalities tailored towards specific industry needs.
What are Cribl's most important features?Cribl sees extensive use in industries prioritizing efficient data management and cost optimization. Organizations leverage its capabilities to connect between different data sources, including cloud environments, improving both data handling and storage efficiency. Its customization options appeal to firms needing specific industry compliance and operational enhancements.
Grafana is an open-source visualization and analytics platform that stands out in the field of monitoring solutions. Grafana is widely recognized for its powerful, easy-to-set-up dashboards and visualizations. Grafana supports integration with a wide array of data sources and tools, including Prometheus, InfluxDB, MySQL, Splunk, and Elasticsearch, enhancing its versatility. Grafana has open-source and cloud options; the open-source version is a good choice for organizations with the resources to manage their infrastructure and want more control over their deployment. The cloud service is a good choice if you want a fully managed solution that is easy to start with and scale.
A key strength of Grafana lies in its ability to explore, visualize, query, and alert on the collected data through operational dashboards. These dashboards are highly customizable and visually appealing, making them a valuable asset for data analysis, performance tracking, trend spotting, and detecting irregularities.
Grafana provides both an open-source solution with an active community and Grafana Cloud, a fully managed and composable observability offering that packages together metrics, logs, and traces with Grafana. The open-source version is licensed under the Affero General Public License version 3.0 (AGPLv3), being free and unlimited. Grafana Cloud and Grafana Enterprise are available for more advanced needs, catering to a wider range of organizational requirements. Grafana offers options for self-managed backend systems or fully managed services via Grafana Cloud. Grafana Cloud extends observability with a wide range of solutions for infrastructure monitoring, IRM, load testing, Kubernetes monitoring, continuous profiling, frontend observability, and more.
The Grafana users we interviewed generally appreciate Grafana's ability to connect with various data sources, its straightforward usability, and its integration capabilities, especially in developer-oriented environments. The platform is noted for its practical alert configurations, ticketing backend integration, and as a powerful tool for developing dashboards. However, some users find a learning curve in the initial setup and mention the need for time investment to customize and leverage Grafana effectively. There are also calls for clearer documentation and simplification of notification alert templates.
In summary, Grafana is a comprehensive solution for data visualization and monitoring, widely used across industries for its versatility, ease of use, and extensive integration options. It suits organizations seeking a customizable and scalable platform for visualizing time-series data from diverse sources. However, users should be prepared for some complexity in setup and customization and may need to invest time in learning and tailoring the system to their specific needs.
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