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Gigamon Deep Observability Pipeline vs Google Cloud Data Loss Prevention comparison

 

Comparison Buyer's Guide

Executive Summary

Review summaries and opinions

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

Categories and Ranking

Gigamon Deep Observability ...
Ranking in Data Loss Prevention (DLP)
33rd
Average Rating
8.6
Reviews Sentiment
6.5
Number of Reviews
9
Ranking in other categories
Application Performance Monitoring (APM) and Observability (42nd), Event Monitoring (15th), Security Information and Event Management (SIEM) (41st), Web Application Firewall (WAF) (34th), Advanced Threat Protection (ATP) (24th), Network Packet Broker (NPB) (1st), Network Detection and Response (NDR) (16th)
Google Cloud Data Loss Prev...
Ranking in Data Loss Prevention (DLP)
28th
Average Rating
9.0
Reviews Sentiment
5.2
Number of Reviews
2
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of August 2026, in the Data Loss Prevention (DLP) category, the mindshare of Gigamon Deep Observability Pipeline is 0.5%, up from 0.2% compared to the previous year. The mindshare of Google Cloud Data Loss Prevention is 1.0%, up from 0.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Loss Prevention (DLP) Mindshare Distribution
ProductMindshare (%)
Google Cloud Data Loss Prevention1.0%
Gigamon Deep Observability Pipeline0.5%
Other98.5%
Data Loss Prevention (DLP)
 

Featured Reviews

TN
Senior Relationship Banker at Joint stock Commercial Bank for Foreign Trade of V
Experience boosts operational efficiency while performance sees room for improvement
I don't have specific information on whether it was purchased on the AWS marketplace or somewhere else. I am working with Dynatrace Operator. I am also working with Algosec, Alluvio, CrowdStrike, Firemon, Gigamon Deep Observability Pipeline, and other solutions. I think it's a good tool, and I am satisfied with it. We have not stored cloud workloads with Gigamon Deep Observability Pipeline yet; we are still on-premises. The technical support takes about one to two hours to respond, which is acceptable. I am satisfied with the scalability of the product. The interface is good.
RaviUpadhyay - PeerSpot reviewer
Security Consultant at HCLSoftware
Automated scans have classified sensitive data and protect privacy in complex environments
When someone asks where sensitive data is located and to classify it, they would start working manually and would take four or five months to detect only that sensitive data. Google Cloud Data Loss Prevention helps significantly. They have a predefined template, and whatever category comes under sensitive data has been researched with almost 99% accuracy and included in the template. A person needs to attach the template and scan their data. Once initiated, it will take time, such as 24 hours or 48 hours, depending on the data size. Once the template is applied and the system scans it, a tagging report of the sensitive data locations is returned. A report is available, and what previously would have taken a month can now be achieved by Google Cloud Data Loss Prevention services in detecting sensitive PII data within 48 hours maximum, even if the data size is larger. Once the report is available, the person would know where the sensitive data is located. Dealing with sensitive data is the next question. If data is not to be shared, it has to be hidden, masked, or changed. All kinds of things can be applied to dealing with that data. Google Cloud Data Loss Prevention has another feature available called de-identification services, which deals with sensitive data in applications or production environments.

Quotes from Members

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

Pros

"It offers straightforward integration."
"The solution is straightforward to set up."
"The most valuable feature is NetFlow."
"We use Gigamon for network visibility."
"It has high stability."
"The Pipeline's Comprehensive Insights into data flows have helped improve operational efficiency and security."
"The most valuable feature for improving network visibility with Gigamon is the packet filtering capability."
"The tool's most valuable feature is the encryption feature. From a security perspective, the solution hasn't significantly strengthened our security posture. However, it has greatly improved performance by streamlining encryption processes and avoiding encryption at multiple layers. This has also simplified troubleshooting, as we can whitelist certain processes."
"These tasks can be achieved by Google Cloud Data Loss Prevention services in a programmatic way, very quickly and very efficiently."
"It is user- friendly and has a easy integration."
 

Cons

"The security should be improved."
"In terms of improvement, while the initial setup is not overly complicated, we did encounter a few issues."
"It only inspects a specific kind of traffic. There should be different kinds of use cases."
"The challenge is monitoring the cloud network."
"The Gigamon Deep Observability Pipeline should have a feature showing the traffic flow within its platform. Currently, customers have to use separate tools for monitoring, which is inconvenient. If it had its visibility feature, it would make monitoring easier and more complete without needing extra tools."
"The graphical user interface could be improved."
"Its filtering feature needs improvement."
"Gigamon Deep Observability Pipeline needs to improve its performance. I face issues with performance because we use SPAN, and the SPAN traffic is not good."
"Improvement are made as per client requirement."
"Google Cloud Data Loss Prevention has a system, but it is not very mature."
 

Pricing and Cost Advice

"I would rate the solution as expensive, around an eight or nine out of ten. There are other competitive solutions available."
"The solution's price is reasonable."
"The solution is highly-priced."
Information not available
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909,725 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Financial Services Firm
14%
Manufacturing Company
9%
Computer Software Company
9%
Comms Service Provider
8%
Comms Service Provider
13%
Financial Services Firm
10%
University
10%
Construction Company
9%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business3
Midsize Enterprise1
Large Enterprise5
No data available
 

Questions from the Community

What needs improvement with Gigamon Deep Observability Pipeline?
Gigamon Deep Observability Pipeline needs to improve its performance. I face issues with performance because we use SPAN, and the SPAN traffic is not good. They need to improve their performance.
What is your primary use case for Gigamon Deep Observability Pipeline?
I am working with Gigamon Deep Observability Pipeline and Firemon, and I have been working with it for a year.
What advice do you have for others considering Gigamon Deep Observability Pipeline?
I don't have specific information on whether it was purchased on the AWS marketplace or somewhere else. I am working with Dynatrace Operator. I am also working with Algosec, Alluvio, CrowdStrike, F...
What needs improvement with Google Cloud Data Loss Prevention?
When someone asks where sensitive data is located and to classify it, they would start working manually and would take four or five months to detect only that sensitive data. Google Cloud Data Loss...
What advice do you have for others considering Google Cloud Data Loss Prevention?
Further strategies can be defined based on specific use cases. For example, in an R&D company where doctors are dealing with sensitive data and need to share it, if two doctors are sitting in d...
What is your experience regarding pricing and costs for Google Cloud Data Loss Prevention?
Pricing is based on data size. Google offers different pricing models, and they provide good discounts when someone commits to a long-term engagement with their Google services.
 

Also Known As

Gigamon, GigaSecure
No data available
 

Overview

 

Sample Customers

Amica Insurance, College of William & Mary, Gamma, IntercontinentalExchange, OppenheimerFunds
Information Not Available
Find out what your peers are saying about Gigamon Deep Observability Pipeline vs. Google Cloud Data Loss Prevention and other solutions. Updated: August 2026.
909,725 professionals have used our research since 2012.