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BigID Next vs Cube 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 AI Data Analysis
8th
Average Rating
8.2
Reviews Sentiment
7.0
Number of Reviews
15
Ranking in other categories
Data Loss Prevention (DLP) (12th), Data Governance (8th), Data Privacy Management Software (1st), Data Security Posture Management (DSPM) (6th)
Cube
Ranking in AI Data Analysis
34th
Average Rating
8.6
Reviews Sentiment
6.5
Number of Reviews
4
Ranking in other categories
Embedded BI (10th)
 

Mindshare comparison

As of July 2026, in the AI Data Analysis category, the mindshare of BigID Next is 0.8%, down from 23.1% compared to the previous year. The mindshare of Cube is 0.3%. It is calculated based on PeerSpot user engagement data.
AI Data Analysis Mindshare Distribution
ProductMindshare (%)
BigID Next0.8%
Cube0.3%
Other98.9%
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.
Peter Jefferson - PeerSpot reviewer
Customer Success Manager at Unilever Inc.
Automated reporting has freed time for deeper analysis and improved budget and variance reviews
A specific example of how my team uses Cube in our day-to-day work is that above all, Cube has vastly enhanced our ability to get financial reporting done quickly and free up our time to really dig deep into various accounts. This has greatly improved the accuracy of our financial results beyond what you would even believe. The clean portal and organization help my team by making it easy to navigate and the data collected is very clean and managed in an understandable manner, hence making it very easy to make data-driven decisions. Regarding the features, customer service is great, customization of financial reports, ease of integration with other tools seamlessly, continuous system testing and upgrades, and easy creation of monthly and P&L variance analysis. Data import and export is smooth and efficient. Monthly reporting and analysis is easy to pull and update. The positive impact Cube has had on my organization includes additional time for analysis, less than budgeted spend, and more accurate financial results resulting in better decisions. The error rate has reduced from 40 to 50%. The reduction in errors has affected my team and the business overall by improving speed and efficiency for month-end close processes. Better consolidation of data for long-term trend analysis is evident, and easy P&L creation and variance analysis has been great.

Quotes from Members

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

Pros

"One of the most valuable things in a data-focused world is a tool, a technology that's data-centric, not trying to master data management or whatever else. It's a source of truth for what data an organization holds, giving it the ability to catalog, categorize, and understand its data."
"BigID is more advanced than Microsoft Purview when it comes to machine learning and AI development tools."
"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."
"Data classification is highly effective due to its automatic capabilities."
"BigID has one of the best technical support teams."
"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 data classification offered by the tool can help companies improve their security strategy"
"BigID integrates well with our other products."
"Cube completes my tasks very easily and takes less time, allowing me to deliver any project in a timely manner to our clients."
"NPS improved to approximately eight out of ten for our feature, and internally ticket handling times decreased, allowing reallocation of resources to higher-impact projects."
"Implementation was super smooth, and within two weeks we were up and running and the metrics were exposed in our app."
 

Cons

"BigID is expensive. I prefer McAfee."
"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."
"The tool currently lacks security features."
"One area where BigID can be improved is the UI, which has a lot of bugs."
"More classifications about different states are needed"
"In terms of what could be improved, when you're looking in a BigID file, you cannot really get the whole file. You have to export it to download it to another platform that allows you to completely view it, or run a program. That was one of the things that was really a disappointing point for me. Not to be able to view everything. There's a lot more data, but you can't get it all at once."
"There are some shortcomings when it comes to Calvirus authentication, which is not yet supported by BigID."
"The challenge we encountered was with data connection across multiple databases. We struggled with configuring the data connection successfully. However, with the assistance of dynamic teams, we resolved this issue."
"I did not see any return on investment from Cube."
"There is no way to create a real template that is not exposed directly in the UI."
"Cube's interface can be challenging for non-technical users, needing clearer use-case examples to ease integration into workflows."
"Cube can be improved by enhancing data refresh over multiple tabs."
 

Pricing and Cost Advice

"I think that BigID's pricing is very reasonable."
"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 solution is expensive."
"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."
Information not available
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Top Industries

By visitors reading reviews
Financial Services Firm
20%
Manufacturing Company
10%
Insurance Company
8%
Comms Service Provider
6%
No data available
 

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...
What is your experience regarding pricing and costs for Cube?
The cost is around $1,500 per month. The exact number is not coming to my mind, but it is approximately $1,500 or $200 per month.
What needs improvement with Cube?
There is something that should be improved. We are providing metrics on email, and in the email industry we have both transactional emails and marketing emails. We have different models for these, ...
What is your primary use case for Cube?
We needed Cube in order to have a robust semantic layer on top of our ClickHouse database to avoid exposing our projection database directly in our app, and we needed to have sub-second latency met...
 

Comparisons

No data available
 

Overview

 

Sample Customers

Home Depot, Grant Thornton LLP, Cimpress, Fidelity Investments
Information Not Available
Find out what your peers are saying about BigID Next vs. Cube and other solutions. Updated: June 2026.
902,894 professionals have used our research since 2012.