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Google Cloud Datalab vs KNIME Business Hub comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Jun 3, 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

Google Cloud Datalab
Ranking in Data Science Platforms
18th
Average Rating
7.8
Reviews Sentiment
6.4
Number of Reviews
6
Ranking in other categories
Data Visualization (16th)
KNIME Business Hub
Ranking in Data Science Platforms
3rd
Average Rating
8.2
Reviews Sentiment
6.8
Number of Reviews
63
Ranking in other categories
Data Mining (1st)
 

Mindshare comparison

As of June 2026, in the Data Science Platforms category, the mindshare of Google Cloud Datalab is 1.7%, up from 1.0% compared to the previous year. The mindshare of KNIME Business Hub is 5.1%, down from 12.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms Mindshare Distribution
ProductMindshare (%)
KNIME Business Hub5.1%
Google Cloud Datalab1.7%
Other93.2%
Data Science Platforms
 

Featured Reviews

LJ
System Architect at UST Global España
dashboards are good and data visualization is more meaningful for the end-user
Access is always via URL, and unless your network is fast, it would be a little tough in India. In India, if we had a faster network, it would be easier. In a big data environment, like when forcing your database with over a billion records, it can be tough for the end-user to manage the data. You need to have a single entity system in each environment. It's not because of GCP, but it would be great to have options like MongoDB or other similar tools in GCP. Then, we wouldn't always need to connect to the cloud and execute SQL queries. Even if your application is always connected to its database, the processing can be cumbersome. It shouldn't be so complicated. Once the data is collected, it should be easily sorted.
NataliaRaffo - PeerSpot reviewer
Co Founder & Chief Data Officer Cdo at NTT DATA
Workflow automation has accelerated advanced analytics and machine learning delivery
Sometimes it is a little bit difficult to use some nodes when we have many large-scale data, for example, CSV files with a large amount of data. It is sometimes difficult to try to import the data in KNIME Business Hub nodes because I think that some features that are in the CSV in text, for example, large text, is difficult for KNIME Business Hub to import these fields. I don't know why, but it is very difficult. We need to try to use different nodes for importing the data, such as File Reader and CSV Reader. However, I think that it is always the features that have much text, it is difficult for KNIME Business Hub to understand and import this information. I don't know why, or maybe I don't know if we don't know what the better option is to configure the node to import all the CSV or the data set. However, we have always had this problem. In some nodes, sometimes it is the same because sometimes, for example, I have a CSV and in my CSV, I have a feature that is, for example, a date. When I import this data set in the File Reader node, I have problems with this field because it is a date, but the problem is that it imports it as text, for example. We try to use their nodes that convert text to date, but sometimes it is difficult, and it is not immediate to transform the text into a date. So we needed to convert the text into a date in the CSV, and then import it again in the KNIME Business Hub node and try to have a good read of this field. I know that KNIME Business Hub has some nodes to convert text to date and others, but sometimes it is difficult to use these nodes. I don't know why. Maybe it needs a specific format for the date and we need to transform our feature in this option. So sometimes it is a large process to convert these features. However, sometimes we need to investigate and search for other nodes, and try with other nodes to import these cases.

Quotes from Members

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

Pros

"The APIs are valuable."
"For me, it has been a stable product."
"All of the features of this product are quite good."
"In MLOps, when we are designing the data pipeline, the designing of the data pipeline is easy in Google Cloud."
"The infrastructure is highly reliable and efficient, contributing to a positive experience."
"Google Cloud Datalab is very customizable."
"The most valuable feature is the data wrangling, which is what I mainly use it for."
"With KNIME, I am able to get that process down to under one minute, with data broken down into individual tabs."
"We are able to automate several functions which were done manually, and I can integrate several data sets quickly and easily to support analytics."
"What I like most about KNIME is that it's user-friendly. It's a low-code, no-code tool, so students don't need coding knowledge. You can make use of different kinds of nodes. KNIME even has a good description of each node."
"The most valuable is the ability to seamlessly connect operators without the need for extensive programming."
"The product is user-friendly."
"It is very fast to develop solutions."
"I've never had any problems with stability."
 

Cons

"There is room for improvement in the graphical user interface. So that the initial user would use it properly, that would be a good option."
"The interface should be more user-friendly."
"Connectivity challenges for end-users, particularly when loading data, environments, and libraries, need to be addressed for an enhanced user experience."
"The product must be made more user-friendly."
"Even if your application is always connected to its database, the processing can be cumbersome. It shouldn't be so complicated."
"We have also encountered challenges during our transition period in terms of data control and segmentation. The management of each channel and data structure as it has its own unique characteristics requires very detailed and precise control. The allocation should be appropriate and the complexity increases due to the different time zones and geographic locations of our clients. The process usually involves migrating the existing database sets to gcp and ensure data integrity is maintained. This is the only challenge that we faced while navigating the integers of the solution and honestly it was an interesting and unique experience."
"KNIME could improve when it comes to large data markets."
"I've had some problems integrating KNIME with other solutions."
"It's very general in terms of architecture, and as a result, it doesn't support efficient running. That is, the speed needs to be improved."
"I wish there were more video training resources for KNIME. The current videos are very short, and most learning is text-based. Longer training sessions would be helpful, especially for complex flowchart use cases. Webinars focusing on starting projects and analyzing data would also be beneficial."
"KNIME is not scalable."
"For graphics, the interface is a little confusing. So, this is a point that could be improved."
"There are some parameters that I would like to have at a bigger scale. The upper limit of one node that tries to find spots or areas in photos was too small for us. It would need to be bigger."
"If they had a more structured training model it would be very helpful."
 

Pricing and Cost Advice

"The product is cheap."
"It is affordable for us because we have a limited number of users."
"The pricing is quite reasonable, and I would give it a rating of four out of ten."
"For beginners, the free desktop version is very attractive, but the full server version can be more expensive. I have only used the free version and it offers a fair pricing system. I have been promoting it to others without any compensation or request from the company, simply because I am enthusiastic about it. I am not aware of the pricing for the server version, but it seems to be widely used."
"The client versions are mostly free, and we pay only for the KNIME server version. It's not a cheap solution."
"KNIME is a cheap product. I currently use KNIME's open-source version."
"It is free of cost. It is GNU licensed."
"While there are certain limitations in functionality, you can still utilize it efficiently free of charge."
"KNIME is free as a stand-alone desktop-based platform but if you want to get a KNIME server then you can find the cost on their website."
"There is no cost for using KNIME because it is an open-source solution, but you have to pay if you need a server."
"KNIME is an open-source tool, so it's free to use."
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Top Industries

By visitors reading reviews
Financial Services Firm
19%
Construction Company
18%
University
7%
Outsourcing Company
6%
Financial Services Firm
12%
Manufacturing Company
9%
University
8%
Educational Organization
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Small Business21
Midsize Enterprise16
Large Enterprise32
 

Questions from the Community

What needs improvement with Google Cloud Datalab?
Access is always via URL, and unless your network is fast, it would be a little tough in India. In India, if we had a faster network, it would be easier. In a big data environment, like when forcin...
What is your primary use case for Google Cloud Datalab?
It's for our daily data processing, and there's a batch job that executes it. The process involves more than ten servers or systems. Some of them use a mobile network, some are ONTAP networks, and ...
What advice do you have for others considering Google Cloud Datalab?
Overall, I would rate it a nine out of ten. Google Cloud is very good. Once you go through the features of Google Cloud, it's a good idea to get a GCP certification so you have an idea of how it ca...
What is your experience regarding pricing and costs for KNIME?
I rate the product’s pricing a seven out of ten, where one is cheap and ten is expensive.
What needs improvement with KNIME?
I would describe KNIME Decision Hub as somewhat helpful in making data-driven decisions more efficient. It could have been a scalable decisioning as a service at the back end, but it's not working ...
What is your primary use case for KNIME?
I mainly use KNIME Business Hub currently for data ETLs and then it meets with predictive analytics. Sometimes I utilize it for forecasting, but mostly it's predictive analytics. I have utilized bo...
 

Also Known As

No data available
KNIME Analytics Platform
 

Overview

 

Sample Customers

Information Not Available
Infocom Corporation, Dymatrix Consulting Group, Soluzione Informatiche, MMI Agency, Estanislao Training and Solutions, Vialis AG
Find out what your peers are saying about Google Cloud Datalab vs. KNIME Business Hub and other solutions. Updated: June 2026.
900,747 professionals have used our research since 2012.