BigID Next vs SAP Data Hub [EOL] comparison

Why PeerSpot?

BigID and SAP are both solutions in the Data Governance category. Additionally, 100% of BigID users are willing to recommend the solution, compared to 66% of SAP users who would recommend it.

BigID Next

Read 15 BigID Next reviews

11,257 Views
6,529 Comparison Views

100% willing to recommend

SAP Data Hub [EOL]

Read 3 SAP Data Hub [EOL] reviews

66% willing to recommend

BigID Next

SAP Data Hub [EOL]

Comparison Buyer's Guide

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Executive SummaryUpdated on Apr 15, 2026

SAP Data Hub EOL and BigID Next compete in the data management category. BigID Next seems to have the upper hand due to its advanced data privacy and governance capabilities, which remain unmatched in the market.

Features: SAP Data Hub EOL provides centralized data processing, seamless integration with SAP environments, and effective workflow automation. BigID Next is recognized for its data privacy capabilities, comprehensive data discovery, and innovative data governance features.

Ease of Deployment and Customer Service: SAP Data Hub EOL is straightforward to deploy for SAP users, promoting quick adoption within SAP systems. BigID Next offers platform independence and comprehensive training, though its implementation can be complex.

Pricing and ROI: SAP Data Hub EOL offers lower setup costs for SAP infrastructure users, enhancing system efficiency. BigID Next requires higher initial investment but delivers greater ROI through its focus on compliance and data privacy, appealing to businesses needing robust data protection.

To learn more, read our detailed Data Governance Report (Updated: October 2026).

Buyer's Guide

Data Governance

October 2026

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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

Average Rating

8.2

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

Data Loss Prevention (DLP) (13th), Data Governance (7th), Data Privacy Management Software (2nd), Data Security Posture Management (DSPM) (4th), AI Data Analysis (9th), Data Security Platforms (DSP) (1st)

SAP Data Hub [EOL]

Average Rating

7.6

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

No ranking in other categories

Featured Reviews

Aniruddha Nath

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.

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Vijaya Macherla

GTM Lead at Capgemini

The solution is seamless, but the database sometimes leads to confusion

We used to have multiple different kinds of databases, which internally, had different compliance levels. Retention management is very different now. If the policy is live and the claim has been completed, I couldn't archive the claim. I needed to keep a reference integrity of that claim and understand which policy paid out the claim. With this solution, the policy came in six months ago and qualified for archiving. The claim had been paid and in every environment, the claim had been closed, including the reporting system, the claims system, etc. With the payment set gateway, I can just go and archive. But, we had a hard time during this process. I rate the overall solution a seven out of ten.

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Quotes from Members

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

Pros

"Although I was serving the client rather than my own organization, BigID has made scans faster and more efficient, and the DSR results are much more accurate."

"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."

"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."

"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 most valuable feature of BigID is its large number of classifiers, which allow us to scan for specific data such as SSN numbers."

"It provides a unified view across different databases and supports a wide range of data source types, including cloud and on-premises systems."

"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 has one of the best technical support teams."

More BigID Next pros

"SAP is one of the most seamless ERPs that have integrated SAP archiving within Excel. I have not seen this with any other database."

"The most valuable feature is the S/4HANA 1909 On-Premise"

"Its connection to on-premise products is the most valuable. We mostly use the on-premise connection, which is seamless. This is what we prefer in this solution over other solutions. We are using it the most for the orchestration where the data is coming from different categories. Its other features are very much similar to what they are giving us in open source. Their push-down approach is the most advantageous, where they push most of the processing on to the same data source. This means that they have a serverless kind of thing, and they don't process the data inside a product such as Data Hub. They process the data from where the data is coming out. If it is coming from HANA, to capture the data or process it for analytics, orchestration, or management, they go to the HANA database and give it out. They don't process it on Data Hub. This push-down approach increases the processing speed a little bit because the data is processed where it is sitting. That's the best part and an advantage. I have used another product where they used to capture the data first and then they used to process it and give it. In Data Hub, it is in reverse. They process it first and give it, and then they put their own manipulations. They lead in terms of business functions. No other solution has business functions already implemented to perform business analysis. They have a lot of prebuilt business functions for machine learning and orchestration, which we can use directly to get an analysis out from the existing data. Most of the data is sitting as enterprise data there. That's a major advantage that they have."

"They lead in terms of business functions, and no other solution has business functions already implemented to perform business analysis, with a lot of prebuilt business functions for machine learning and orchestration that we can use directly to get an analysis out from the existing enterprise data."

"Having this solution enables us to approach our clients to upgrade their databases, and we upgrade them according to their business requirements."

Cons

"One area where BigID can be improved is the UI, which has a lot of bugs."

"One concern I have with BigID is regarding certain scans, like the multi-scan. The issue is that we can stop and retrieve these scans, but once they start, they go through an enumeration process."

"BigID is expensive. I prefer McAfee."

"BigID's user interface was problematic as it was not very user-friendly, though I believe it improved over time."

"BigID needs improvement in terms of automation."

"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."

"The tool currently lacks security features."

More BigID Next cons

"The company has everything offshore."

"In 2018, connecting it to outside sources, such as IoT products or IoT-enabled big data Hadoop, was a little complex. It was not smooth at the beginning. It was unstable. It took a lot of time for the initial data load. Sometimes, the connection broke, and we had to restart the process, which was a major issue, but they might have improved it now. It is very smooth with SAP HANA on-premise system, SAP Cloud Platform, and SAP Analytics Cloud. It could be because these are their own products, and they know how to integrate them. With Hadoop, they might have used open-source technologies, and that's why it was breaking at that time. They are providing less embedded integration because they want us to use their other products. For example, they don't want to go and remove SAP Analytics Cloud and put everything in Data Hub. They want us to use SAP Analytics Cloud somewhere else and not inside the Data Hub. On the integration part, it lacks real-time analytics, and it is slow. They should embed the SAP Analytics Cloud inside Data Hub or support some kind of analysis. They do provide some analysis, but it is not extensive. They are moreover open source. So, we need a lot of developers or data scientists to go in and implement Python algorithms. It would be better if they can provide their own existing algorithms and give some connections and drop-down menus to go and just configure those. It will make things really quick by increasing the embedded integrations. It will also improve the process efficiency and processing power. Its performance needs improvement. It is a little slow. It is not the best in the market, and there are other products that are much better than this. In terms of technology and performance, it is a little slow as compared to Microsoft and other data orchestration products. I haven't used other products, but I have read about those products, their settings, and the milliseconds that they do. In Azure Purview, they say that they can copy, manage, or transform the data within milliseconds. They say that they can transform 100 gigabytes of data within three to five seconds, which is something SAP cannot do. It generally takes a lot of time to process that much amount of data. However, I have never tested out Azure."

"Its performance needs improvement. It is a little slow. It is not the best in the market, and there are other products that are much better than this."

"Nowadays there are some inconsistencies in data bases, however, they upgrade and release the versions to market."

Pricing and Cost Advice

"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."

"I think that BigID's pricing is very reasonable."

"The solution is expensive."

"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 Cloud is very expensive, but SAP HANA previous service is okay."

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Top Industries

By visitors reading reviews

Financial Services Firm

17%

Manufacturing Company

11%

Comms Service Provider

Insurance Company

Outsourcing Company

14%

Manufacturing Company

14%

Construction Company

10%

Financial Services Firm

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	5
Large Enterprise	11

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...

See all answers

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...

See all answers

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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Comparisons

OneTrust DataGovernance vs BigID Next

Compared 9% of the time

Varonis Platform vs BigID Next

Compared 6% of the time

Securiti vs BigID Next

Compared 6% of the time

Cyera vs BigID Next

Compared 6% of the time

OneTrust Privacy vs BigID Next

Compared 5% of the time

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Oracle Data Integrator (ODI) vs SAP Data Hub [EOL]

Compared 9% of the time

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Compared 7% of the time

Informatica Intelligent Data Management Cloud (IDMC) vs SAP Data Hub [EOL]

Compared 6% of the time

SSIS vs SAP Data Hub [EOL]

Compared 5% of the time

WhereScape RED vs SAP Data Hub [EOL]

Compared 4% of the time

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Product Reports

Buyer's Guide

BigID Next

October 2026

Download BigID Next product report

Buyer's Guide

Data Governance

October 2026

Download SAP Data Hub [EOL] product report

Overview

BigID Next offers advanced data discovery, classification, and governance tools, streamlining compliance with privacy laws while integrating seamlessly with Microsoft platforms.

BigID Next provides comprehensive data management through machine learning-enhanced capabilities, supporting data discovery and classification for both structured and unstructured data. By simplifying processes for GDPR and CCPA compliance, and facilitating data scanning and mapping across databases, it optimizes data management. Automation is central to its design, with solutions for DSAR requests, organizing data with security labels, and ensuring a holistic organizational data view. Improvements in navigation, bug fixes, and scan reliability remain essential, along with enhancing classifiers for broader region coverage.

What features does BigID Next offer?

User-Friendly Interface: Easily navigable for streamlined data operations.
Microsoft Integration: Seamless compatibility with Microsoft platforms.
Data Scanning Capabilities: Efficiently scans structured and unstructured data.
Data Classification and Discovery: Identifies and categorizes sensitive data.
Security Labels: Supports predefined and custom security labels.
Automation for PII Requests: Automates privacy request management.
Compliance Adherence: Aligns with GDPR and CCPA requirements.
Scheduling Scans: Facilitates planned data assessments.
Machine Learning: Enhances data mapping, auditing, and management.

What benefits should users look for?

Enhanced Compliance: Supports adherence to major privacy laws like GDPR and CCPA.
Data Mapping Efficiency: Improves data locating and classification.
Automation Features: Saves time with automated data request handling.
Comprehensive Integration: Works well with existing security tools.
Holistic Data View: Offers clear insights into data storage and use.

BigID Next is commonly implemented in industries needing robust data governance, such as finance and healthcare, where data privacy and compliance with regulations are critical. It aids in scanning and classifying extensive data volumes, helping businesses maintain regulatory compliance while managing data risks effectively.

BigID

The SAP® Data Hub solution enables sophisticated data operations management. It gives you the capability and flexibility to connect enterprise data and Big Data and gain a deep understanding of data and information processes across sources and systems throughout the distributed landscape. The unified solution provides visibility and control into data opportunities, integrating cloud and on-premise information and driving data agility and business value. Distributed processing power enables greater speed and efficiency.

SAP

Sample Customers

Home Depot, Grant Thornton LLP, Cimpress, Fidelity Investments

Kaeser Kompressoren, HARTMANN

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