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BigID Next vs Cohesity DataProtect comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Jan 22, 2026

Review summaries and opinions

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

ROI

Sentiment score
7.3
BigID Next offers strong ROI through compliance, data management integration, cost savings, automation, and reduced staffing, avoiding fines.
Sentiment score
6.6
Cohesity DataProtect delivers cost, time savings, enhances efficiency, simplifies backups, and ensures swift recovery, achieving ROI within months.
We have seen returns across all three aspects: fewer employees needed, money saved, and time saved with BigID.
Senior Security Consultant at a consultancy with 10,001+ employees
It is one of the best tools in the market.
Senior Manager at KPMG
I have seen a return on investment from using BigID, particularly as it is a regulatory and compliance tool that helps avoid potential penalties for non-compliance.
Senior Security Consultant at a consultancy with 10,001+ employees
Using Cohesity DataProtect is easier to manage, and it simplifies various components into one architecture, reducing the need for extensive human resources to manage backups.
Evangelist / CTO at fgnext
 

Customer Service

Sentiment score
6.5
BigID Next's support is praised for responsiveness, efficiency, and high customer satisfaction, despite occasional delays and time-consuming initial contact.
Sentiment score
7.8
Cohesity DataProtect offers knowledgeable and fast support, though some face challenges with regional differences and global case management.
Even when I faced issues within the BigID environment, such as unsuccessful connections or new errors, the BigID team resolved them.
Senior Security Consultant at a consultancy with 10,001+ employees
I would rate the customer support a six because you cannot directly reach out to L3 or L2 support if there's a major issue.
Senior Security Consultant at a consultancy with 10,001+ employees
BigID has one of the best technical support teams.
Senior Manager at KPMG
For the support, I can provide a rating of four only because they initially provide some steps, but later say they are not sure, which is a problem in a production environment.
Specialist at HCLSoftware
The support can depend on the region, and for larger customers, I advise having a Technical Account Manager for better assistance.
Evangelist / CTO at fgnext
 

Scalability Issues

Sentiment score
6.7
BigID Next is scalable with mixed opinions, excelling in large environments but facing data handling and presentation challenges.
Sentiment score
7.7
Cohesity DataProtect is highly regarded for its seamless scalability, supporting both small and large environments with ease.
I have added very large data sources to the BigID environment, and it remains stable.
Senior Security Consultant at a consultancy with 10,001+ employees
BigID is scalable, allowing you to purchase as many scanners as you want.
Senior Security Consultant at a consultancy with 10,001+ employees
Cohesity DataProtect is built on a scale-out architecture, which means it can effectively scale to meet various needs.
Evangelist / CTO at fgnext
 

Stability Issues

Sentiment score
7.5
BigID Next is often seen as reliable with some stability concerns but praised for data security and ease of use.
Sentiment score
7.7
Cohesity DataProtect is praised for stability, quick support resolution, minor glitches, reliable updates, and consistent performance in diverse environments.
BigID is generally stable, however, there is a noted issue with bulk tagging that can affect scan results.
Senior Associate - IT Governance and Compliance at Fulcrum Digital Inc
On the whole, any problems were more related to hardware limitations rather than issues with Cohesity DataProtect itself.
Evangelist / CTO at fgnext
 

Room For Improvement

BigID Next needs enhancements in file access, security, automation, UI navigation, deployment, data governance, and support features.
Cohesity DataProtect needs improved restoration, customization, robust integration, and enhanced security features to boost user satisfaction and functionality.
There is also an issue with incident tagging, where all objects get tagged without an option to untag specific ones, and reverting changes is only possible through MongoDB Central, which can lead to data loss for certain periods.
Senior Associate - IT Governance and Compliance at Fulcrum Digital Inc
I want them to focus on data mapping, assessment, automation workflow, and privacy incident management.
Senior Manager at KPMG
BigID deserves recognition for the data discovery part, which has been wonderful and quite accurate, along with the confidence level process that allows us to fine-tune results for better accuracy from the database.
Assistant Manager - Cyber : Digital Privacy and Trust at Deloitte
There is room to improve the user interface of Cohesity DataProtect for more intuitive navigation.
Specialist at HCLSoftware
While there are improvements to be made, such as providing support for older systems like IBM iSeries and tandem systems from HP, the solution overall shifts from older methods to modern practices.
Evangelist / CTO at fgnext
 

Setup Cost

BigID Next offers premium, capacity-based pricing; valued by large enterprises for advanced features, less feasible for smaller businesses.
Cohesity DataProtect offers cost-effective, straightforward pricing with bundled storage, quick setup, negotiable discounts, and affordable annual support.
The pricing is competitive in the market, however, I need to ask for the right price.
Senior Manager at KPMG
BigID might be expensive as it involves various paid services, like data retention and graphic rights management.
Senior Associate - IT Governance and Compliance at Fulcrum Digital Inc
I find Cohesity DataProtect to be expensive.
Technical Director at Procloud
 

Valuable Features

BigID Next offers a user-friendly design, seamless Microsoft integration, and powerful data discovery, classification, and protection capabilities.
Cohesity DataProtect offers fast backups, easy scalability, cloud integration, and robust features like deduplication, unified search, and ransomware protection.
BigID simplifies things by integrating both data protection and data privacy in one environment, making it easier for end users.
Senior Security Consultant at a consultancy with 10,001+ employees
One of the best features of BigID is its strength in data discovery and governance.
Senior Manager at KPMG
The most valuable feature of BigID is its large number of classifiers, which allow us to scan for specific data such as SSN numbers.
Senior Associate - IT Governance and Compliance at Fulcrum Digital Inc
The platform is based on a scale-out architecture with each node having compute, RAM, SSD, and HDD.
Evangelist / CTO at fgnext
Cohesity DataProtect's architecture ensures that agent installations automatically reflect in the dashboard, allowing for seamless integration into backup jobs.
Specialist at HCLSoftware
Some of the most valuable features of Cohesity DataProtect for me include instant mass restore, anomaly detection, and its ability to handle large data volumes effectively.
Technical Director at Procloud
 

Categories and Ranking

BigID Next
Ranking in AI Data Analysis
2nd
Average Rating
8.2
Reviews Sentiment
7.0
Number of Reviews
15
Ranking in other categories
Data Loss Prevention (DLP) (7th), Data Governance (6th), Data Privacy Management Software (2nd), Data Security Posture Management (DSPM) (4th)
Cohesity DataProtect
Ranking in AI Data Analysis
8th
Average Rating
9.0
Reviews Sentiment
7.3
Number of Reviews
75
Ranking in other categories
Backup and Recovery (7th), Cloud Backup (10th)
 

Mindshare comparison

As of January 2026, in the AI Data Analysis category, the mindshare of BigID Next is 2.7%, down from 16.7% compared to the previous year. The mindshare of Cohesity DataProtect is 0.5%, up from 0.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.
AI Data Analysis Market Share Distribution
ProductMarket Share (%)
BigID2.7%
Cohesity DataProtect0.5%
Other96.8%
AI Data Analysis
 

Featured Reviews

Aniruddha Nath - PeerSpot reviewer
Senior Security Consultant at a consultancy with 10,001+ employees
Data discovery has transformed compliance workflows and automation now speeds up requests and remediation
The best feature that BigID offers is data discovery and classification, which is the most powerful engine. It allows connecting to many different data sources, ranging from cloud to on-premises to structured to unstructured data. If there is no connector available, you can build your own classifiers as well. Regarding the custom classifier option, you can build custom classifiers using regular expressions, and I have done that if you know how to create regular expressions. Custom connectors are something you create to connect to a database where the connector is not available. BigID has positively impacted my organization as it's a very powerful tool, especially with the increasing regulatory compliances for different countries such as GDPR, CCPA, and India's recent DPDPA act. Having these tools in place greatly helps organizations avoid any penal charges for not being compliant with the regulatory compliances. For example, regarding compliance or reduced risks for my clients, the DSAR process I was talking about allows organizations to respond quickly to user data deletion requests under GDPR law, which traditionally has a 30-day or 60-day timeline. In larger organizations, when the number of requests is high, it becomes tedious. However, using DSAR automation with BigID, it's almost instantaneous; instead of 30 days, you can respond in just one day to what users have requested.
SM
Evangelist / CTO at fgnext
Adopting advanced convergence and seamless management elevates data protections
While there are improvements to be made, such as providing support for older systems like IBM iSeries and tandem systems from HP, the solution overall shifts from older methods to modern practices. Customers looking for features that older systems provided might find gaps, but these are typically for very specific needs.
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Top Industries

By visitors reading reviews
Financial Services Firm
22%
Insurance Company
9%
Computer Software Company
8%
Manufacturing Company
6%
Financial Services Firm
13%
Manufacturing Company
10%
Computer Software Company
10%
Government
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business5
Large Enterprise11
By reviewers
Company SizeCount
Small Business19
Midsize Enterprise22
Large Enterprise43
 

Questions from the Community

What do you like most about BigID?
I like BigID's in-depth discovery and scanning capabilities, especially for unstructured data. This feature is a standout compared to competitors. The tool's data classification capabilities are i...
What needs improvement with BigID?
One improvement I would suggest is addressing the intermittent failures of BigID scans, as there are times when some errors occur. I think the BigID team is aware of this and works on resolving iss...
What is your primary use case for BigID?
BigID's main use case is connecting to various data sources to perform the data discovery process, classify the data within those systems, and identify sensitive information across various structur...
What do you like most about Cohesity DataProtect?
Several features enable us to perform fast recovery, such as instant fast recovery. All our virtual machines protected with the product can be quickly restored to another healthy environment with m...
What needs improvement with Cohesity DataProtect?
There is room to improve the user interface of Cohesity DataProtect for more intuitive navigation, despite being content with its existing features.
 

Also Known As

No data available
Cohesity
 

Overview

 

Sample Customers

Home Depot, Grant Thornton LLP, Cimpress, Fidelity Investments
Tribune Media
Find out what your peers are saying about BigID Next vs. Cohesity DataProtect and other solutions. Updated: December 2025.
881,114 professionals have used our research since 2012.