We performed a comparison between Trellix Network Detection and Response and Vectra AI based on real PeerSpot user reviews.
Find out in this report how the two Network Detection and Response (NDR) solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."The server appliance is good."
"The sandbox feature of FireEye Network Security is very good. The operating system itself has many features and it supports our design."
"Its ability to find zero-day threats, malware and anything malicious has greatly improved my customer's organization, especially for protecting the users' browser."
"The features that I find most valuable are the MIR (Mandiant Incident Response) for checks on our inbound security."
"The most valuable feature of the solution stems from how it allows users to do the investigation part. Another important part of the product that is valuable is associated with how it gives information to users in the form of a storyline."
"The product has helped improve our organization by being easy to use and integrate. This saves time, trouble and money."
"The scalability has not been a problem. We have deployed the product in very high bandwidth networks. We have never had a problem with the FireEye product causing latency issues within our networks."
"The most valuable feature is the network security module."
"The initial setup was pretty straightforward."
"It has reduced the time it takes to respond to attacks. That comes back to the proactive point. It makes us able to lower down in the kill chain, we can react now, rather than reacting to incidents that happened, we can see an instant, in some cases, as it's being implemented, or as it's being launched."
"Vectra AI can bring the ability to detect intrusion on the network more so than legacy IDS tools."
"It does a reliable job of parsing out the logs of all the network traffic so that we can ingest them into our SIEM and utilize them for threat hunting and case investigations. It is pretty robust and reliable. The administration time that we spend maintaining it or troubleshooting it is very low. So, the labor hour overhead is probably our largest benefit from it. We spend 99% of our time in Vectra investigating cases, responding to incidents, or hunting, and only around 1% of our time is spent patching, troubleshooting, or doing anything else. That's our largest benefit from Vectra."
"The biggest feature for us, because we are heavy Microsoft users, is its integration with Office 365. On top of Vectra AI, we use all of the Microsoft security platforms, such as Defender ATP and Sentinel. Having full integration and a central platform to look at all of the threats that are coming through from the different platforms is a huge benefit for us."
"One of the key advantages for us is we define a 24/7 service around it. We use far more of Vectra alerts than we do with our SIEM product because we understand that when we get an alert from Vectra we actually need to do something about it."
"Vectra AI helped our team be more productive and save time. We have less work thanks to it."
"The fact that we get the visualization of what's happening on our network, which is a way of improving our security in-depth is most valuable."
"The analytics could be better. It seems heavily influenced by the McAfee and FireEye integration, and that integration still isn't seamless."
"It doesn't connect with the cloud, advanced machine learning is not there. A known threat can be coming into the network and we would want the cloud to look up the problem. I would also like to see them develop more file replication and machine learning."
"It would be a good idea if we could get an option to block based upon the content of an email, or the content of a file attachment."
"The product's integration capabilities are an area of concern where improvements are required."
"As far as future inclusions, it would be useful to display more threat intelligence, such as the actual area of the threat and the origin of the web crawling (Tor and Dark Web)."
"We'd like the potential for better scaling."
"Cybersecurity posture has room for improvement."
"The problem with FireEye is that they don't allow VM or sandbox customization. The user doesn't have control of the VMs that are inside the box. It comes from the vendor as-is. Some users like to have control of it. Like what type of Windows and what type of applications and they have zero control over this."
"There is room for improvement in the documentation. We would like to have more details on how it detects what we see."
"Some of their integrations with other sources of data, like external threat feeds, took a bit more work than I had hoped to get integrated."
"One thing which I have found where there could be improvement is with regard to the architecture, a little bit: how the brains and sensors function. It needs more flexibility with regard to the brain. If there were some flexibility in that regard, that would be helpful, because changing the mode of the brain is complex. In some cases, the change is permanent. You cannot revert it."
"An area for improvement in Vectra AI is reporting because it currently needs some details. For example, when you download a report from Vectra AI, you won't see complete information about the alerts or triggers. Another area for improvement in the tool is that sometimes, an alert has high severity, yet it's marked as low severity. Vectra AI should have a mechanism to change the severity level from low to high or critical."
"The solution needs to become more proactive. When Vectra AI is the primary solution in an environment - like it is in our case - you must work on response time. We have a small team so response time at endpoint level is vital."
"Vectra Recall could be utilized much more, and I'm seeing some indications of that today with the investigative components. I use the Visualize feature to visualize components and dashboards a lot. I'm interested in new ways to build automated searches or having them leveraged already from Vectra."
"The main improvement I can see would be to integrate with more external solutions."
"In education as a sector, we are looking at AI a lot in terms of how it can be used as part of the teaching and learning side of things. It would be great to have Vectra AI look at a better way to enhance the security posture related to the AI tools in our portfolio."
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Trellix Network Detection and Response is ranked 7th in Network Detection and Response (NDR) with 37 reviews while Vectra AI is ranked 2nd in Network Detection and Response (NDR) with 42 reviews. Trellix Network Detection and Response is rated 8.4, while Vectra AI is rated 8.6. The top reviewer of Trellix Network Detection and Response writes "Offers in-depth investigation capabilities, integrates well and smoothly transitioned from a lower-capacity appliance to a higher one". On the other hand, the top reviewer of Vectra AI writes "Integrates well with other security solutions and provides good technical support". Trellix Network Detection and Response is most compared with Fortinet FortiSandbox, Palo Alto Networks WildFire, Fortinet FortiGate, Zscaler Internet Access and Zabbix, whereas Vectra AI is most compared with Darktrace, ExtraHop Reveal(x), Cisco Secure Network Analytics, Arista NDR and Splunk User Behavior Analytics. See our Trellix Network Detection and Response vs. Vectra AI report.
See our list of best Network Detection and Response (NDR) vendors.
We monitor all Network Detection and Response (NDR) reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.
