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CloudCheckr vs Data Hub 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:
 

ROI

Sentiment score
6.6
CloudCheckr CMx High Security users report significant ROI through reduced manual efforts, optimized spending, and automated invoicing.
Sentiment score
2.9
Data Hub boosts efficiency via time savings and error reduction, but Atlan is quicker for specific tasks, with mixed ROI feedback.
It has reduced manual efforts that would otherwise be spent checking where spending is occurring and ensuring all teams use resources correctly.
Dev Ops Engineer at a construction company with 11-50 employees
I have seen a return on investment of 100%, with significant cost avoidance and measurable savings within the first few months of deployment.
Sr PreSales Cloud Architect at a outsourcing company with 10,001+ employees
I've seen a return on investment, as the savings are concrete, measurable, and they show up directly in the AWS bill.
Top Engineer at a tech vendor with 5,001-10,000 employees
Atlan has a better approach compared to Data Hub.
Data Quality Engineer at truelogic
Data Hub centralizes data cataloging and classification, saving us from having to disclose PII column information to teams not utilizing it.
Software Engineer L2 at a tech vendor with 1,001-5,000 employees
It is very helpful in building data quality for the company, leading to approximately thirty percent improvement in efficiency.
Finance Feedback Committee at MB Shinsei Finance Limited Liability Company
 

Customer Service

Sentiment score
6.2
CloudCheckr's customer service is praised for responsiveness, but some encounter delays requiring account rep involvement for resolution.
Sentiment score
3.8
Data Hub's customer service is responsive and helpful, with useful forums and webinars, though some report occasional setup challenges.
The additional support ended up taking longer than expected, with responses that did not meet our need for detailed and technical assistance.
Sr PreSales Cloud Architect at a outsourcing company with 10,001+ employees
Sometimes support needs to be reached, but they are very responsive and supportive.
Dev Ops Engineer at a construction company with 11-50 employees
The customer support for CloudCheckr is fantastic.
Director, Trust Operations Analytics at a tech vendor with 1,001-5,000 employees
When I was working with Atlan, and needed support, they were very good at attending to my requests directly.
Data Quality Engineer at truelogic
Customer support for Data Hub is quite good.
Manager - Projects at Cognizant
Customer support for Data Hub is very genuine, and they are responsive and attentive.
Senior Software Engineer 2 at Porch
 

Scalability Issues

Sentiment score
8.1
CloudCheckr is praised for scalability and efficiency in managing diverse cloud environments despite concerns about handling large data volumes.
Sentiment score
5.4
Data Hub scales efficiently, handling diverse data sources, though optimization is needed for extensive datasets, supporting data mesh.
If tomorrow I were to contract AWS or Google Cloud Services, I could manage them from the same place.
IT Director at Instituto de Innovacion Empresarial
It scales well for MSPs and large enterprises, allowing for management of hundreds of accounts and tens of thousands of resources while retaining performance and visibility.
Sr PreSales Cloud Architect at a outsourcing company with 10,001+ employees
We have successfully onboarded over 1000 datasets from various sources without any issues.
Senior Software Engineer 2 at Porch
Data Hub's scalability is advantageous, as we onboard data from over one hundred fifty tables in SQL Server to Snowflake, and adding new tables to Data Hub is not time-consuming.
Manager - Projects at Cognizant
Data Hub's scalability is very easy, as we were able to add users and new datasets very quickly and smoothly.
Data Quality Engineer at truelogic
 

Stability Issues

Sentiment score
8.2
CloudCheckr is a stable, reliable cloud optimization tool with high ratings, though minor issues and slow queries are noted.
Sentiment score
8.0
Data Hub and Acryl Data are highly stable, reliable, and comparable to Oracle with minimal downtime and rare minor issues.
CloudCheckr is stable and rock solid.
Top Engineer at a tech vendor with 5,001-10,000 employees
Since I've been using Data Hub, it has always been very stable; I can say it was one hundred percent stable.
Data Quality Engineer at truelogic
It is quite reliable and on par with what is created using the Oracle database.
Lead Business Analyst at a tech vendor with 10,001+ employees
When I used Data Hub, I did not experience any lagging, crashing, or downtime.
Senior Data Engineer at a tech services company with 1-10 employees
 

Room For Improvement

CloudCheckr requires improved integration, easier use, better reporting, clearer pricing, faster performance, and enhanced tool compatibility.
Data Hub needs better integration, automation, UI, analytics, and security, with enhancements in metadata, memory, and AI functions.
CloudCheckr is a powerful and feature-rich tool with abundant metrics.
Dev Ops Engineer at a construction company with 11-50 employees
Another area is drift analysis; there have been complaints about tracking optimization opportunities, such as how to track opportunities identified in January and whether they were resolved in February.
Sr PreSales Cloud Architect at a outsourcing company with 10,001+ employees
The data does not work in real time; rather, it takes between one and three days to show you the usage.
IT Director at Instituto de Innovacion Empresarial
Providing consulting or support with professionals who are qualified to use Data Hub would be interesting, along with providing training and certifications for the tool so that those who are implementing it can specialize increasingly in its features.
Data Quality Engineer at truelogic
The impact is very positive, and there are many benefits for us using Data Hub because it was easier to make data governance, create centralized metadata management, improve data discoverability, and manage data in general.
Software Engineer at a tech vendor with 10,001+ employees
I wonder if it can automate the classification exercise, possibly using AI to auto-classify PII direct and indirect items.
Director at a university with 1-10 employees
 

Setup Cost

CloudCheckr offers competitive, tiered pricing aligned with Azure consumption, providing good value and requiring a CloudCheckr CMx license.
Enterprise users find Data Hub affordable and effective, connecting multiple data sources with a $100,000 budget, with favorable feedback.
Overall, the pricing was quite convenient and represented good value for money.
Dev Ops Engineer at a construction company with 11-50 employees
Pricing is feature-tiered under the MSP licensing, and I would say the pricing was quite competitive and fair.
Sr PreSales Cloud Architect at a outsourcing company with 10,001+ employees
I won't pretend it's cheap, but we've saved multiples of what we pay for it, so the conversation with finance is straightforward.
Top Engineer at a tech vendor with 5,001-10,000 employees
Regarding experience with pricing, setup cost, and licensing, I think if we have a budget of one hundred thousand US dollars, we will be able to deploy a reasonable version and connect to a number of data sources.
Director at a university with 1-10 employees
It costs about zero since, if we win the setup, it probably results in no cost.
Finance Feedback Committee at MB Shinsei Finance Limited Liability Company
 

Valuable Features

CloudCheckr offers simplicity, cost visibility, actionable insights, multi-cloud integration, and security, leading to significant savings and efficiency.
Data Hub enhances data exploration, collaboration, and governance with seamless integrations, metadata management, and user-friendly interface, boosting efficiency.
The cost visibility and reporting are really valuable, and the dashboard is informative and enables good decision-making.
Dev Ops Engineer at a construction company with 11-50 employees
What makes CloudCheckr easy for me to use is its intuitive interface.
Director, Trust Operations Analytics at a tech vendor with 1,001-5,000 employees
The best features CloudCheckr offers include out-of-the-box security and compliance check features that provide over 35 different types of compliance checks at no cost, best practice checks, and alerts.
Sr PreSales Cloud Architect at a outsourcing company with 10,001+ employees
Data Hub became a single source of truth for metadata, supporting both compliance requirements and day-to-day operational needs.
Software Engineer at a tech vendor with 10,001+ employees
Data Hub has positively impacted our organization by bringing the tribal knowledge that resides with team members into a single place where users can discover and understand the data elements before they make use of it.
Director at a university with 1-10 employees
Having a tool that shows the data lineage from the source until the target tables helps us a lot.
Data Quality Engineer at truelogic
 

Categories and Ranking

CloudCheckr
Ranking in AI Observability
19th
Average Rating
7.8
Reviews Sentiment
6.8
Number of Reviews
13
Ranking in other categories
Cloud Management (9th), Cloud Cost Management (9th), Managed Cloud Services (5th)
Data Hub
Ranking in AI Observability
8th
Average Rating
8.2
Reviews Sentiment
4.8
Number of Reviews
22
Ranking in other categories
Metadata Management (4th)
 

Mindshare comparison

As of August 2026, in the AI Observability category, the mindshare of CloudCheckr is 0.6%, up from 0.1% compared to the previous year. The mindshare of Data Hub is 0.6%. It is calculated based on PeerSpot user engagement data.
AI Observability Mindshare Distribution
ProductMindshare (%)
Data Hub0.6%
CloudCheckr0.6%
Other98.8%
AI Observability
 

Featured Reviews

AbhishekGupta2 - PeerSpot reviewer
Sr PreSales Cloud Architect at a outsourcing company with 10,001+ employees
Centralized cloud costs have boosted savings while reporting and user experience still need work
The best features CloudCheckr offers include out-of-the-box security and compliance check features that provide over 35 different types of compliance checks at no cost, best practice checks, and alerts. Another valuable feature is the multi-cloud overview, providing unified reporting across AWS and Azure while allowing us to create different types of dashboards based on who logs into the platform. Additionally, from an MSP standpoint, there is good ease of deployment, especially the billing and chargeback functionality for a reseller or managed services provider. CloudCheckr has positively impacted my organization by helping us manage multiple customers and tens of thousands of resources while retaining performance and visibility due to its multi-cloud support. We do not have to worry about jumping from one platform to another, and the better MSP support is beneficial from a billing and chargeback automation standpoint. The integration in compliance helps identify missing areas within our customer environments and improves them. On average, it has helped us provide approximately 15 to 20% savings through right-sizing or idle resource elimination. These are some of the immediate cost savings our customers have experienced after implementing recommendations from the tool.
Akashkhurana Hirana - PeerSpot reviewer
Senior Software Engineer 2 at Porch
Metadata management has streamlined lineage tracking and data discovery for our teams
The best features Data Hub offers include its integration capability with many popular tools like Apache Airflow, Snowflake, dbt, Looker, Apache Kafka, and BigQuery. These tools provide us with data in various places, and we commonly use Apache Airflow for the DAG, while utilizing BigQuery as our database and Apache Kafka for consuming messaging queues. Data Hub easily connects with all these tools and features excellent data discovery and visualization capabilities. We can see data visibility, where it comes from, its upstream and downstream relationships. If we remove a column, we can assess the impact of that change. Furthermore, if there are duplicate datasets being used by different teams that do not communicate regularly, onboarding all data to Data Hub allows us to identify these duplicates easily. Out of all those features, I believe data discovery and impact analysis are the most valuable for my team because when we want to add or drop a column, we can assess the impact analysis to understand the downstream effects. This helps us know who owns a dataset, and we can easily contact the owner. Tracking the data lineage back to the source table is also a key benefit. Data Hub has positively impacted my organization by significantly reducing manual work that was previously needed to identify upstream and downstream data relationships, as well as recognizing duplicate datasets. If a data contract is broken, we now easily get notified of those issues, making the process much easier and more efficient. It is particularly useful for data engineers and platform teams to check for problems directly within Data Hub. Data Hub has saved our team a lot of time. For example, in a large company like Porch, if I want to know whether a specific dataset exists, I can check Data Hub, as it serves as a centralized point for managing the metadata of our data. While it does not contain all data, it does contain the metadata necessary for understanding the dataset's origin. If a dataset does not exist, I can simply see who the owner is and reach out to them, which reduces the dependency on others by providing direct access to information in Data Hub.
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Top Industries

By visitors reading reviews
Construction Company
15%
Outsourcing Company
12%
Manufacturing Company
12%
Comms Service Provider
7%
Financial Services Firm
18%
Outsourcing Company
12%
Construction Company
10%
Manufacturing Company
9%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business5
Midsize Enterprise1
Large Enterprise10
By reviewers
Company SizeCount
Small Business5
Midsize Enterprise7
Large Enterprise15
 

Questions from the Community

What is your experience regarding pricing and costs for CloudCheckr ?
My experience with pricing, setup cost, and licensing reflects that it uses custom pricing based on your cloud spend, which is pretty standard for this category. I won't pretend it's cheap, but we'...
What needs improvement with CloudCheckr ?
The interface could be improved because it is too dense and overloaded with too many charts and too much information on each screen. Latency is also something important to take into account. The da...
What is your primary use case for CloudCheckr ?
My main use case for CloudCheckr is checking the Azure cloud costs of my SaaS service. A specific example of how I use CloudCheckr to check those Azure cloud costs with my SaaS service is that my A...
What needs improvement with Data Hub?
Data Hub can be improved with easy accessibility. I think integration with other environments is needed to enhance accessibility.
What is your primary use case for Data Hub?
My main use case for Data Hub is for data governance, specifically the use of data lineage and data catalog. I use Data Hub for data governance and data lineage in my day-to-day work by checking th...
What advice do you have for others considering Data Hub?
I do not have any advice to give to others looking into using Data Hub. I found this interview valuable and do not think anything needs to change for the future. My overall review rating for Data H...
 

Also Known As

CloudCheckr CMx High Security, CloudCheckr CMP
Acryl Data
 

Overview

 

Sample Customers

Accenture, Logitech, Ingram, Cloudar, Infor, DXC, Cornell University, DLT, Lumen, Lightstream, Choice Hotels, B-Tech, SmileShark, PTP, Explicity, JCH Technology, Siemens Mobility
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Find out what your peers are saying about CloudCheckr vs. Data Hub and other solutions. Updated: June 2026.
909,725 professionals have used our research since 2012.