Compare ExtraHop Reveal(x) vs. Splunk User Behavior Analytics

ExtraHop Reveal(x) is ranked unranked in Intrusion Detection and Prevention Software while Splunk User Behavior Analytics is ranked 4th in Intrusion Detection and Prevention Software with 10 reviews. ExtraHop Reveal(x) is rated 0, while Splunk User Behavior Analytics is rated 8.2. On the other hand, the top reviewer of Splunk User Behavior Analytics writes "Easy to configure and easy to use solution that integrates with many applications and scripts ". ExtraHop Reveal(x) is most compared with Darktrace, Cisco Stealthwatch and Vectra AI, whereas Splunk User Behavior Analytics is most compared with Darktrace, Cisco Stealthwatch and Microsoft ATA.
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372,906 professionals have used our research since 2012.
Quotes From Members

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

Pricing and Cost Advice
Information Not Available
Pricing varies based on the packages you choose and the volume of your usage.The licensing costs is around 10,000 dollars.There are additional costs associated with the integrator.My biggest complaint is the way they do pricing... You can never know the pricing for next year. Every single time you adjust to something new, the price goes up. It's impossible to truly budget for it. It goes up constantly.I hope we can increase the free license to be more than 5 gig a day. This would help people who want to introduce a POC or a demo license for the solution.

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Ranking
Unranked
In Intrusion Detection and Prevention Software
Views
7,081
Comparisons
4,939
Reviews
10
Average Words per Review
524
Avg. Rating
8.1
Top Comparisons
Compared 52% of the time.
Compared 8% of the time.
Also Known As
Reveal(x), RevealxCaspida, Splunk UBA
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ExtraHop Networks
Splunk
Overview

Reveal(x) provides the visibility, insights, and answers that security analysts need to respond quickly and confidently to the highest priority threats against their organization's critical assets. It starts by automatically discovering and classifying every device communicating across the network, and using machine-learning driven behavioral analysis to detect anomalous and malicious activity.

Splunk User Behavior Analytics is a behavior-based threat detection is based on machine learning methodologies that require no signatures or human analysis, enabling multi-entity behavior profiling and peer group analytics – for users, devices, service accounts and applications. It detects insider threats and external attacks using out-of-the-box purpose-built that helps organizations find known, unknown and hidden threats, but extensible unsupervised machine learning (ML) algorithms, provides context around the threat via ML driven anomaly correlation and visual mapping of stitched anomalies over various phases of the attack lifecycle (Kill-Chain View). It uses a data science driven approach that produces actionable results with risk ratings and supporting evidence that increases SOC efficiency and supports bi-directional integration with Splunk Enterprise for data ingestion and correlation and with Splunk Enterprise Security for incident scoping, workflow management and automated response. The result is automated, accurate threat and anomaly detection.
Offer
Learn more about ExtraHop Reveal(x)
Learn more about Splunk User Behavior Analytics
Sample Customers
Wood County Hospital8 Securities, AAA Western, AdvancedMD, Amaya, Cerner Corporation, CJ O Shopping, CloudShare, Crossroads Foundation, 7-Eleven Indonesia
Top Industries
No Data Available
VISITORS READING REVIEWS
Software R&D Company19%
Financial Services Firm17%
Comms Service Provider14%
Insurance Company7%
Find out what your peers are saying about Cisco, GFI, Darktrace and others in Intrusion Detection and Prevention Software. Updated: October 2019.
372,906 professionals have used our research since 2012.
We monitor all Intrusion Detection and Prevention Software 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.
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