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Google Cloud Data Loss Prevention vs Netskope Data Loss Prevention (DLP) 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

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
Netskope Data Loss Preventi...
Ranking in Data Loss Prevention (DLP)
16th
Average Rating
8.2
Reviews Sentiment
6.2
Number of Reviews
5
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 Google Cloud Data Loss Prevention is 1.0%, up from 0.9% compared to the previous year. The mindshare of Netskope Data Loss Prevention (DLP) is 2.1%, down from 3.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Loss Prevention (DLP) Mindshare Distribution
ProductMindshare (%)
Netskope Data Loss Prevention (DLP)2.1%
Google Cloud Data Loss Prevention1.0%
Other96.9%
Data Loss Prevention (DLP)
 

Featured Reviews

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.
reviewer1595751 - PeerSpot reviewer
Information Security Manager at a tech vendor with 1,001-5,000 employees
Has improved sensitive data detection while requiring better support for data-at-rest scanning and classification
Data in transit works quite well and operates in near real-time. However, data at rest scanning operates under separate licensing, and it would be beneficial to examine applications where the location of sensitive data is unknown. Netskope Data Loss Prevention (DLP) could improve data-at-rest scanning capabilities. Regarding DLP-specific improvements, data-at-rest scanning could be enhanced in terms of the applications supported, as coverage is currently limited to a restricted set of enterprise applications. Expanding application coverage would be beneficial. Additionally, data-at-rest scans should be made easier and faster to execute. Most solutions lack Data Security Posture Management (DSPM) functionality, and this capability is not yet mature. A significant limitation is that Netskope Data Loss Prevention (DLP) does not support out-of-the-box data classification. Third-party integrations must be relied upon instead, whereas having built-in data classification support would be advantageous.

Quotes from Members

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

Pros

"It is user- friendly and has a easy integration."
"These tasks can be achieved by Google Cloud Data Loss Prevention services in a programmatic way, very quickly and very efficiently."
"I find Netskope Data Loss Prevention (DLP) easier and more appealing than Zscaler."
"Netskope Data Loss Prevention (DLP) provides predefined templates, indexed data matching, EDM, and OCR capabilities, and the role functionality provides significant information, and considerable automation has been built on top of the platform using the available APIs."
"The product provides visibility to manage sensitive data and control access."
"The product is flexible."
"The Real-Time Analytics and Reporting capabilities of Netskope Data Loss Prevention (DLP) are good and up to the mark."
 

Cons

"Improvement are made as per client requirement."
"Google Cloud Data Loss Prevention has a system, but it is not very mature."
"I rate the pricing a seven out of ten. The pricing is moderate."
"Netskope Data Loss Prevention (DLP) can be improved primarily because we were looking for any other provider due to the ZTNA feature that we were scoping from Netskope."
"Technical support has been rated low. Numerous bugs have been discovered in terms of functionality, and the support team takes considerable time to resolve these issues."
"I have not seen any benefits from this real-time analysis at this time."
"The product should be compatible with multiple file formats."
 

Pricing and Cost Advice

Information not available
"The pricing is moderate."
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909,725 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Comms Service Provider
13%
Financial Services Firm
10%
University
10%
Construction Company
9%
Financial Services Firm
12%
Healthcare Company
9%
Manufacturing Company
9%
Comms Service Provider
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
No data available
 

Questions from the Community

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.
What needs improvement with Netskope Data Loss Prevention (DLP)?
Data in transit works quite well and operates in near real-time. However, data at rest scanning operates under separate licensing, and it would be beneficial to examine applications where the locat...
What is your primary use case for Netskope Data Loss Prevention (DLP)?
Netskope Data Loss Prevention (DLP) is being used as a Secure Services Engine (SSE) solution for the CASB solution, Shadow IT detection, and Secure Web Gateway capabilities. The primary focus is on...
What advice do you have for others considering Netskope Data Loss Prevention (DLP)?
Remediation involves blocking specific communications when users attempt to upload sensitive information. Users should be provided with an interface to request exceptions in real-time for business-...
 

Overview

Find out what your peers are saying about Google Cloud Data Loss Prevention vs. Netskope Data Loss Prevention (DLP) and other solutions. Updated: August 2026.
909,725 professionals have used our research since 2012.