Vectra AI and Wazuh are competing in the cybersecurity space, focusing on threat detection and response. Vectra AI appears to have an advantage due to its advanced automation and machine learning capabilities, enhancing threat prioritization and alert management.
Features:Vectra AI offers advanced threat detection with AI capabilities, consolidates alerts to reduce fatigue, and monitors east-west traffic efficiently. Its Cognito Recall and Detect ensure comprehensive data analysis with minimal manual effort. Wazuh provides integration with SIEM systems, compliance checks, and active response, while being customizable and flexible for various systems.
Room for Improvement:Vectra AI requires improved SIEM integration, better alert filtering, and enhanced packet management. It also needs to unify DHCP data handling. Wazuh lacks native threat intelligence, struggles with Unix systems management, and needs better cloud integration and scalability. Users report limited support unless separately purchased.
Ease of Deployment and Customer Service:Vectra AI primarily offers on-premises setups with hybrid and public cloud options, supported by responsive technical teams. Wazuh relies on its open-source community and supplemental support packages. Wazuh's deployment depends on the environment, offering less personalized service compared to Vectra AI.
Pricing and ROI:Vectra AI is a premium service with costs based on IP addresses, providing a significant reduction in attack response times and analyst workload. It offers substantial ROI through risk mitigation. Wazuh is free, incurring costs only for optional support services or additional infrastructure, making it a budget-friendly choice for basic security needs.
I have seen value in security cost savings with Wazuh, as using proprietary EDR versions could save us substantial money.
The support is quite reliable depending on the service engineer assigned.
When I create tickets, the response is fast, and issues are solved promptly.
They responded quickly, which was crucial as I was on a time constraint.
The documentation is good and provides clear instructions, though it's targeted at those with technical backgrounds.
We use the open-source version of Wazuh, which does not provide paid support.
It can accommodate thousands of endpoints on one instance, and multiple instances can run for different clients.
Currently, I don't see any limitations in terms of scalability as Wazuh can still connect many endpoints.
Scalability depends on the configuration and the infrastructure resources like compute and memory we allocate.
The indexer frequently times out, requiring system restarts.
The stability of Wazuh is largely dependent on maintenance.
The stability of Wazuh is strong, with no issues stemming from the solution itself.
ExtraHop's ability to decrypt encrypted data is a feature that Vectra AI lacks.
You need to have a Linux server, and from the Linux server, you must perform AI tasks, and there is a lot to be handled in the back end.
Neither Vectra nor Darktrace have a function like a status health check on my log sources and traffic sources.
Wazuh could improve by creating videos on YouTube covering installation, use cases, and integration of third-party APIs for different scenarios that other SAAS services provide.
I think Wazuh should improve by introducing AI functionalities, as it would be beneficial to see AI incorporated in the threat hunting and detection functionalities.
The integration modules are insufficiently developed, necessitating the creation of custom integration solutions using tools like Logstash and PubSub.
Vectra is cheaper in terms of pricing and features compared to Darktrace.
It is very acceptable when you compare it with Darktrace, for example.
Wazuh is completely free of charge.
Wazuh is free to use, but there are licensing fees for third parties.
Totaling around two lakh Indian rupees per month.
The main feature of Vectra AI that I find valuable is its focus on the user interface and its approximately two hundred algorithms based on artificial intelligence and machine learning.
There are extensive out-of-box detection capabilities.
With this open source tool, organizations can establish their own customized setup.
The system allows us to monitor endpoints effectively and collect security data that can be utilized across other platforms such as SOAR.
The fact that it is open source means it is always being expanded, which is beneficial for customizing solutions for individual client requests.
Product | Market Share (%) |
---|---|
Wazuh | 10.7% |
Vectra AI | 3.4% |
Other | 85.9% |
Company Size | Count |
---|---|
Small Business | 8 |
Midsize Enterprise | 10 |
Large Enterprise | 27 |
Company Size | Count |
---|---|
Small Business | 25 |
Midsize Enterprise | 15 |
Large Enterprise | 8 |
Vectra AI enhances security operations by pinpointing attack locations, correlating alerts, and providing in-depth visibility across attack lifecycles, ultimately prioritizing threats and improving incident responses.
Vectra AI integrates AI and machine learning to detect anomalies early and supports proactive threat response. Its features like risk scoring, alert correlation, and streamlined SOC efficiency are supplemented by integration with tools like Office 365. Users highlight integration, reporting, and customization challenges, alongside limitations in syslog data and false positive management. They seek enhancements in visualization, UI, TCP replay, endpoint visibility, and tool orchestration, with requests for improved documentation, licensing, and cloud processing innovation.
What are the key features of Vectra AI?In industries like finance, healthcare, and critical infrastructure, Vectra AI is crucial for threat detection and network monitoring. Entities use it for identifying anomalous behaviors and enhancing cybersecurity by responding to network activities and analyzing traffic for potential breaches. It operates on-premises and in hybrid cloud settings, enabling threat detection without endpoint agents and supporting compliance and policy enforcement.
Wazuh offers comprehensive security features like MITRE ATT&CK correlation, log monitoring, and cloud-native infrastructure. It ensures compliance and provides intrusion detection with high scalability and open-source flexibility, ideal for businesses seeking robust SIEM capabilities.
Wazuh stands out in security information and event management by providing efficient log aggregation, vulnerability scanning, and event correlation against MITRE ATT&CK. Its capability to integrate seamlessly with environments, manage compliance, and monitor files makes it suitable for cloud-native infrastructures and financial sectors. Despite its technical support needing enhancement and opportunities for improving AI integration and threat intelligence, its open-source nature and cost-effectiveness make it appealing. Users can leverage custom dashboards powered by Elasticsearch for precise data analysis, even though there is a desire for a more user-friendly interface and better enterprise solution integration. Deployment may be complex, but its features contribute significantly to fortified security postures.
What are the essential features of Wazuh?Industries like finance and cloud infrastructure heavily utilize Wazuh for its security strengths. By monitoring endpoints and ensuring compliance with frameworks, companies can improve security posture and swiftly detect anomalies. The platform's focus on event correlation and alerts for security incidents is particularly beneficial.
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