

Coralogix and Elastic Observability are leading solutions in data observability. Coralogix has the upper hand in terms of user satisfaction with its pricing and support, while Elastic Observability is preferred for its comprehensive features and perceived high value.
Features: Coralogix offers automated data clustering, alerting capabilities, and streamlined monitoring. Elastic Observability provides robust searching, multiple data source integration, and extensive features for users with diverse needs.
Room for Improvement: Coralogix could improve its visualization tools, onboarding process, and user interface. Elastic Observability needs better documentation, more seamless integrations, and enhanced user experience.
Ease of Deployment and Customer Service: Coralogix has a straightforward deployment model with minimal setup time and responsive customer service. Elastic Observability, although more complex to deploy, offers extensive customization options and supportive service.
Pricing and ROI: Coralogix is noted for competitive setup costs and a favorable return on investment. Elastic Observability, though more expensive initially, has a scalable pricing model and long-term ROI that justifies its higher cost.
I have seen a return on investment with Coralogix, particularly in terms of time saved.
I see a return on investment in time saving.
I have seen a return on investment as it is time-saving for debugging since this costs a lot over a period of time.
Elastic Observability has saved us time as it's much easier to find relevant pieces across the system in one screen compared to our own software, and it has saved resources too since the same resources can use less time.
I am satisfied with their response time and overall competence.
They are helpful, especially when we created several custom dashboards.
They were very responsive and thoroughly communicative.
Elastic support really struggles in complex situations to resolve issues.
Their excellent documentation typically helps me solve any issues I encounter.
We have never faced any scalability issues.
Handling scaling with Coralogix is good, as it is easy to scale up or down as my needs change.
I would rate the scalability of Coralogix as easy; it's easy and goes faster.
I rate the scalability of Elastic Observability as a ten, as we have never seen issues even with a lot of data coming in from more customers, provided we have the appropriate configuration.
Elastic Observability seems to have a good scale-out capability.
Elastic Observability is easy in deployment in general for small scale, but when you deploy it at a really large scale, the complexity comes with the customizations.
There are no downtimes, no crashes, or any performance issues that I've noticed since we started using it.
High CPU usage on one pod can be averaged out by others, concealing potential issues.
There are some bugs that come with each release, but they are keen always to build major versions and minor versions on time, including the CVE vulnerabilities to fix it.
It is very stable, and I would rate it ten out of ten based on my interaction with it.
I would rate the stability of Elastic Observability as a ten, as we don't experience any issues.
We require some form of grouping or categorization of logs to identify them better.
Coralogix should have some AI capabilities to auto-detect anomalies and provide suggestions.
If I could improve Coralogix in any way, I would suggest additional customization options for our dashboards.
For instance, if you have many error logs and want to create a rule with a custom query, such as triggering an alert for five errors in the last hour, all you need to do is open the AI bot, type this question, and it generates an Elastic query for you to use in your alert rules.
It lacked some capabilities when handling on-prem devices, like network observability, package flow analysis, and device performance data on the infrastructure side.
Some areas such as AI Ops still require data scientists to understand machine learning and AI, and it doesn't have a quick win with no-brainer use cases.
Despite the expense, I believe it is worth the money to have Coralogix as a tool.
Currently, we are at a very minimal cost, which is around $400 per month since we have reduced our usage.
It is charged based on what we store.
The license is reasonably priced, however, the VMs where we host the solution are extremely expensive, making the overall cost in the public cloud high.
Elastic Observability is cost-efficient and provides all features in the enterprise license without asset-based licensing.
Observability is actually cheaper compared to logs because you're not indexing huge blobs of text and trying to parse those.
I can monitor Kubernetes or Docker platforms as well, and I can integrate with the DevOps chain including Jenkins and all infrastructure code, Terraform, or Ansible.
Coralogix has positively impacted our organization by providing us with a clearer data flow, which allows us to analyze data better and find errors easier using the smart logs it offers.
Out of real-time analytics, cost-efficient storage, and AI-powered insights, the most valuable for my team has been the cost-efficient storage.
The most valuable feature is the integrated platform that allows customers to start from observability and expand into other areas like security, EDR solutions, etc.
the most valued feature of Elastic is its log analytics capabilities.
All the features that we use, such as monitoring, dashboarding, reporting, the possibility of alerting, and the way we index the data, are important.
| Product | Mindshare (%) |
|---|---|
| Elastic Observability | 1.9% |
| Coralogix | 1.1% |
| Other | 97.0% |


| Company Size | Count |
|---|---|
| Small Business | 8 |
| Midsize Enterprise | 7 |
| Large Enterprise | 9 |
| Company Size | Count |
|---|---|
| Small Business | 9 |
| Midsize Enterprise | 4 |
| Large Enterprise | 16 |
Coralogix provides a robust platform for real-time logging and analysis, offering seamless integration with cloud services and DevOps tools to enhance visibility and error detection.
Coralogix is recognized for facilitating efficient log management through intuitive drill-down capabilities and AI-powered anomaly detection. Its platform supports smooth integration with multiple cloud providers and DevOps tools, focusing on ease of use and effective data migration. Users benefit from rich visualization options like dashboards and alerts that accelerate error detection and root cause analysis. Despite its strengths, there is a call for improvements in cost management, user-friendliness, and the expansion of AI features. Users are also requesting better customization, integrated modules, and support for processing large data volumes.
What are Coralogix's standout features?Industries utilize Coralogix for log monitoring and metrics analysis, aiding in debugging, error detection, and performance monitoring with tools like Grafana. Organizations manage cloud application logs, identify system failures, and conduct real-time root cause analysis. Coralogix supports secure data handling, enhancing infrastructure, and transaction management for efficient developer access and log analysis.
Elastic Observability offers a comprehensive suite for log analytics, application performance monitoring, and machine learning. It integrates seamlessly with platforms like Teams and Slack, enhancing data visualization and scalability for real-time insights.
Elastic Observability is designed to support production environments with features like logging, data collection, and infrastructure tracking. Centralized logging and powerful search functionalities make incident response and performance tracking efficient. Elastic APM and Kibana facilitate detailed data visualization, promoting rapid troubleshooting and effective system performance analysis. Integrated services and extensive connectivity options enhance its role in business and technical decision-making by providing actionable data insights.
What are the most important features of Elastic Observability?Elastic Observability is employed across industries for critical operations, such as in finance for transaction monitoring, in healthcare for secure data management, and in technology for optimizing application performance. Its data-driven approach aids efficient event tracing, supporting diverse industry requirements.
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