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BigID Next vs IBM Data Governance 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:
 

Categories and Ranking

BigID Next
Ranking in Data Governance
8th
Average Rating
8.2
Reviews Sentiment
7.0
Number of Reviews
15
Ranking in other categories
Data Loss Prevention (DLP) (11th), Data Privacy Management Software (1st), Data Security Posture Management (DSPM) (5th), AI Data Analysis (7th), Data Security Platforms (DSP) (1st)
IBM Data Governance
Ranking in Data Governance
34th
Average Rating
8.0
Reviews Sentiment
7.5
Number of Reviews
1
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of August 2026, in the Data Governance category, the mindshare of BigID Next is 4.2%, down from 7.0% compared to the previous year. The mindshare of IBM Data Governance is 1.0%, down from 1.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Governance Mindshare Distribution
ProductMindshare (%)
BigID Next4.2%
IBM Data Governance1.0%
Other94.8%
Data Governance
 

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.
Murali B - PeerSpot reviewer
Associate Manager at a consultancy with 10,001+ employees
Provides a single interface to monitor and navigate data quality metrics
One area with room for improvement would be the ability to generate detailed quality reports. Some Python libraries provide quality scores and reports—having that capability within IBM Data Governance would be beneficial. We can see the pass/fail results, but getting additional percentage ratios would add significant value. My experience with IBM Data Governance has mostly been with the GUI. I've noticed some latency when accessing the portal. Also, automating reports can sometimes hang, though that might depend on the overall system. That's where I see the most room for improvement – quicker report generation. Fetching specific data from the IBM Data Governance repository tends to be slower compared to other vendors. For example, Collibra has a more responsive GUI. Retrieving large datasets from the IBM catalog is particularly slow.

Quotes from Members

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

Pros

"Data classification is highly effective due to its automatic capabilities."
"BigID's scanning feature is its most valuable component."
"BigID offers different scan types for data discovery. The most powerful one is the full scan, which scans both data and metadata. However, the metadata scan is faster in comparison."
"The tool's most valuable feature is correlation. Using BigID's data classification capabilities has strengthened our data security. It lets me classify and connect data, which helps me manage data at various classification levels."
"It provides a unified view across different databases and supports a wide range of data source types, including cloud and on-premises systems."
"The features that I have found most valuable are the user experience, the credentialing, and that BigID is user friendly. Additionally, you can deploy to several other Microsoft platforms and you can use it for other things, like a bigger element or a report."
"My experience with BigID has been very positive and memorable, as BigID is simple, straightforward, and reliable when it comes to data discovery and data scanning exercises."
"BigID is more advanced than Microsoft Purview when it comes to machine learning and AI development tools."
"IBM Data Governance improved data analytics operations. During a company merger, we used IBM Data Governance to understand and bridge sample data between systems."
 

Cons

"The tool currently lacks security features."
"More classifications about different states are needed"
"One area where BigID can be improved is the UI, which has a lot of bugs."
"BigID needs improvement in terms of automation."
"Some users find catalog navigation challenging due to the lack of a search-by-column feature, which makes it difficult to locate specific data quickly."
"I want them to focus on data mapping, assessment, automation workflow, and privacy incident management. The privacy tools have not been widely used, and they have not invested much in privacy code privacy tools."
"One improvement I would suggest is addressing the intermittent failures of BigID scans, as there are times when some errors occur."
"BigID is making some forays into the GRC space, and that's a natural progression. I'd like to see that improve so that data governance is better, data risk is identified, and the ability to control and mitigate it."
"One area with room for improvement would be the ability to generate detailed quality reports. Some Python libraries provide quality scores and reports—having that capability within IBM Data Governance would be beneficial."
 

Pricing and Cost Advice

"The solution is not licensed per user but rather based on capacity. For instance, organizations with large amounts of data, such as 50 GB or more, are the ones that typically qualify for BigID."
"The product is expensive, but so are all competitor tools"
"The pricing depends. If you have thousands of data sources to connect and manage, and you struggled with an MDM package in the past, you'll find BigID valuable and even cheap. But if you're a small business, it's probably not the right tool for you."
"The solution is expensive."
"I think that BigID's pricing is very reasonable."
Information not available
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Top Industries

By visitors reading reviews
Financial Services Firm
18%
Manufacturing Company
10%
Insurance Company
8%
Comms Service Provider
6%
Financial Services Firm
13%
Comms Service Provider
10%
Retailer
7%
Insurance Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business5
Large Enterprise11
No data available
 

Questions from the Community

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 advice do you have for others considering BigID?
I have covered information regarding data scanning, data classification, and the DSAR module, as these are the parts I have worked on, apart from developing custom connectors for a few data sources...
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Overview

 

Sample Customers

Home Depot, Grant Thornton LLP, Cimpress, Fidelity Investments
TIAA CREF, Control Risks Group
Find out what your peers are saying about Collibra, Microsoft, Informatica and others in Data Governance. Updated: July 2026.
908,834 professionals have used our research since 2012.