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Data Hub vs ThinkCloud NovaGuard Cloud Security Platform- CNAPP 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

Data Hub
Ranking in AI Observability
16th
Average Rating
8.4
Reviews Sentiment
5.1
Number of Reviews
5
Ranking in other categories
Metadata Management (7th)
ThinkCloud NovaGuard Cloud ...
Ranking in AI Observability
106th
Average Rating
0.0
Number of Reviews
0
Ranking in other categories
AI Software Development (121st), AI Security (112th)
 

Featured Reviews

Henrique dos Anjos - PeerSpot reviewer
Data Quality Engineer at truelogic
Metadata governance has improved data lineage visibility but still needs simpler integrations
I know that the integrations are not easy to do, and I believe it happens because it's a customized solution. There always needs to be software developers to work on this. It's complicated; every time we want to integrate new things or new sources, we need to generate a ticket or a request to another department. When I had my experience with Atlan, for example, I was able to connect different sources in a very user-friendly way. I just needed to set up some configurations and connect to the source without having to be a software developer or develop any code in the back end. It was just a feature in the data catalog that enabled me to connect with different kinds of sources. That's why I think the disadvantage of having a customized solution. Although I think Data Hub itself is a very good tool, years ago I had the opportunity to work with it, but with a clear interface and the open-source solution, which was very clear and easy to connect. At Uber, we need to have a request when we want to integrate new sources. Regarding Data Hub's intuitiveness, regarding analytics, I would say that some quality dimensions are available for us. For example, for each field name or each column in a table, it's possible to see the frequency, how many values we have for a specific type or category, and we can see if there are new or null values, whether the columns are empty or not, along with some metrics. This is regarding the data quality dimensions, such as nullables and things of that nature. That is all we have for features. I remember when I was working with Atlan, there was a feature I liked very much—the possibility to have a sample. When I clicked on a table, I could see a short sample without needing SQL skills. I just clicked the table and could see some values or what the table represents; the data catalog would show a screen with some rows of the table. This feature was very good, but we don't have it in Data Hub the way it is implemented at Uber. I think it would be a very good feature for analytics, and we don't have it at the moment. The integration part could be better, but again, it's because it's a customized solution. I think if they used the native version of the tool, it would be simpler. The integration part and the process of setting up new data quality rules would be important for data governance players like me.
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Top Industries

By visitors reading reviews
Construction Company
16%
Insurance Company
16%
Financial Services Firm
12%
Healthcare Company
8%
No data available
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business2
Midsize Enterprise2
Large Enterprise3
No data available
 

Questions from the Community

What needs improvement with Data Hub?
Data Hub can be improved with more automation; there are some inbuilt automations, such as documenting definitions of data elements using AI, which is useful. I wonder if it can automate the classi...
What is your primary use case for Data Hub?
My main use case for Data Hub is to enrich the metadata to classify for PII data. As an administrator, I crawl a number of data sources and bring the metadata into a single place, then assign the o...
What advice do you have for others considering Data Hub?
I chose seven out of ten because there are better catalogs available in the market that offer more features. The UI, especially when setting up new data sources and crawling them, is a little cumbe...
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Overview

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Find out what your peers are saying about Datadog, SentinelOne, Dynatrace and others in AI Observability. Updated: February 2026.
885,667 professionals have used our research since 2012.