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Google Cloud Datalab vs KNIME Business Hub comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Jul 27, 2025

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
19th
Average Rating
7.8
Reviews Sentiment
6.4
Number of Reviews
6
Ranking in other categories
Data Visualization (18th)
KNIME Business Hub
Ranking in Data Science Platforms
3rd
Average Rating
8.2
Reviews Sentiment
7.1
Number of Reviews
60
Ranking in other categories
Data Mining (1st)
 

Mindshare comparison

As of October 2025, in the Data Science Platforms category, the mindshare of Google Cloud Datalab is 1.1%, up from 1.0% compared to the previous year. The mindshare of KNIME Business Hub is 11.9%, up from 10.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms Market Share Distribution
ProductMarket Share (%)
KNIME Business Hub11.9%
Google Cloud Datalab1.1%
Other87.0%
Data Science Platforms
 

Featured Reviews

Nilesh Gode - PeerSpot reviewer
Easy to setup, stable and easy to design data pipelines
The scalability is average. We have not faced any issues with scalability. There are more than 500 end users using this solution in our company. It is an integral part of the daily operations. The usage pattern is not a one-time thing; employees regularly access and utilize the application. We use it at a global level with a scattered user base. This means that users don't all use the application at the same time. So, around 300 out of 500 employees use the solution, and this usage is spread out throughout the day.
Laurence Moseley - PeerSpot reviewer
Has a drag-and-drop interface and AI capabilities
It's difficult to pinpoint one single feature because KNIME has so many. For starters, it's very easy to learn. You can get started with just a one-hour video. The drag-and-drop interface makes it user-friendly. For example, if you want to read an Excel file, drag the "read Excel file" node from the repository, configure it by specifying the file location, and run it. This gives you a table with all your data. Next, you can clean the data by handling missing values, selecting specific columns you want to analyze, and then proceeding with your analysis, such as regression or correlation. KNIME has over 4,500 nodes available for download. In addition, KNIME offers various extensions. For instance, the text processing extension allows you to process text data efficiently. It's more powerful than other tools like NVivo and Palantir. KNIME also has AI capabilities. If you're unsure about the next step, the AI assistant can suggest the most frequently used nodes based on your previous work. Another valuable feature is the integration with Python. If you need to perform a task that requires Python, you can simply add a Python node, write the necessary code,

Quotes from Members

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

Pros

"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."
"Google Cloud Datalab is very customizable."
"For me, it has been a stable product."
"The APIs are valuable."
"The infrastructure is highly reliable and efficient, contributing to a positive experience."
"The most valuable features of KNIME are its ability to convert your sub-workflow into a node. For example, the workflow has many individual native nodes that can be converted into a single node. This representation has simplified my workflow to a great extent. I can present my workflow in a very compact way."
"Overall KNIME serves its purpose and does a good job."
"It can handle an unlimited amount of data, which is the advantage of using Knime."
"The visual workflow tools for custom and complex tasks always beat raw coding languages with the agility, speed to deliver, and ease of subsequent changes."
"KNIME is very easy to handle and use. Anyone can use it, and it's easy to learn."
"It also has very good fundamental machine learning. It has decision trees, linear regression, and neural nets. It has a lot of text mining facilities as well. It's fairly fully-featured."
"What I like the most is that it works almost out of the box with Random Forest and other Forest nodes."
"KNIME is more intuitive and easier to use, which is the principal advantage."
 

Cons

"The interface should be more user-friendly."
"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."
"Even if your application is always connected to its database, the processing can be cumbersome. It shouldn't be so complicated."
"The product must be made more user-friendly."
"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."
"Connectivity challenges for end-users, particularly when loading data, environments, and libraries, need to be addressed for an enhanced user experience."
"The main issue with KNIME is that it sometimes uses too much CPU and RAM when working with large amounts of data."
"KNIME doesn't handle large datasets or a high number of records well."
"From the point of view of the interface, they can do a little bit better."
"I'd like something that would make it easier to connect/parse websites, although I will fully admit that I'm not as proficient in KNIME as I would like to be, so it could be I'm just missing something."
"Sometimes, we needed more space to handle larger operations, especially since our machines had limited space and memory due to Kubernetes clusters."
"Not just for KNIME, but generally for software and analyzing data, I would welcome facilities for analyzing different sorts of scale data like Likert scales, Thurstone scales, magnitude ratio scales, and Guttman scales, which I don't use myself."
"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."
"The documentation is lacking and it could be better."
 

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."
"Scaling to the on-premises version requires a licensing fee per user that is a bit expensive in comparison to R, Python, and SAS."
"There is no cost for using KNIME because it is an open-source solution, but you have to pay if you need a server."
"I use the open-source version."
"We're using the free academic license just locally. I went for KNIME because they have a free academic license."
"The price for Knime is okay."
"KNIME assets are stand alone, as the solution is open source."
"At this time, I am using the free version of Knime."
"They have different versions, but I am using the open-source one."
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Top Industries

By visitors reading reviews
Financial Services Firm
27%
University
8%
Computer Software Company
8%
Government
8%
Financial Services Firm
11%
University
9%
Manufacturing Company
9%
Computer Software Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Small Business20
Midsize Enterprise16
Large Enterprise29
 

Questions from the Community

What do you like most about Google Cloud Datalab?
Google Cloud Datalab is very customizable.
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 do you like most about KNIME?
Since KNIME is a no-code platform, it is easy to work with.
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 have seen the potential to interact with Python, which is currently a bit limited. I am interested in the newer version, 5.4, when it becomes available. The machine learning and profileration asp...
 

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: September 2025.
872,029 professionals have used our research since 2012.