Google Cloud Datalab vs KNIME Business Hub comparison

Google and Knime are both solutions in the Data Science Platforms category. Google is ranked #19 with an average rating of 7.5, while Knime is ranked #3 with an average rating of 8.0. Google holds a 1.4% mindshare in Data Science Platforms, compared to Knime’s 8.7% mindshare. Additionally, 80% of Google users are willing to recommend the solution, compared to 94% of Knime users who would recommend it.

Google Cloud Datalab

Read 6 Google Cloud Datalab reviews

989 Views
673 Comparison Views

80% willing to recommend

KNIME Business Hub

Read 60 KNIME Business Hub reviews

8,180 Views
5,808 Comparison Views

94% willing to recommend

Google Cloud Datalab

KNIME Business Hub

Comparison Buyer's Guide

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Executive SummaryUpdated on Nov 2, 2025

KNIME Business Hub and Google Cloud Datalab are competing products in the data analytics space, each offering unique strengths. KNIME Business Hub appears to have an edge in terms of ease of use and initial investment, while Google Cloud Datalab stands out for its extensive features and integration benefits, potentially offering superior long-term value.

Features: KNIME Business Hub is appreciated for its comprehensive analytics capabilities, emphasizing user-friendliness, flexibility, and a wide range of integration options. It enables easy ETL operations, integration with R and Weka, and provides a rich algorithm set. Google Cloud Datalab is recognized for its strong integration with other Google Cloud products, enhancing data science workflows. It features robust infrastructure, seamless environment configuration, and good dashboard capabilities for displaying meaningful data.

Room for Improvement: KNIME Business Hub could enhance its advanced analytics capabilities and expand its ecosystem with more integrations. It may also benefit from improving scalability and offering more customizable options. Google Cloud Datalab could improve its user interface for less technical users, simplify its deployment process, and reduce dependency on Google ecosystem tools.

Ease of Deployment and Customer Service: KNIME Business Hub offers a simpler deployment model with rapid implementation and user-friendly support. Google Cloud Datalab, while resource-rich for Google ecosystem deployment, often requires more technical expertise to set up, potentially making KNIME a more straightforward option for organizations.

Pricing and ROI: KNIME Business Hub generally offers competitive pricing, appealing for cost-conscious buyers seeking balanced ROI. Although Google Cloud Datalab commands a higher price, its extensive feature set and integration benefits can yield significant long-term value when integrated into Google Cloud environments, justifying the cost.

To learn more, read our detailed Google Cloud Datalab vs. KNIME Business Hub Report (Updated: December 2025).

Buyer's Guide

Google Cloud Datalab vs. KNIME Business Hub

December 2025

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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

Google Cloud Datalab

Ranking in Data Science Platforms

19th

Average Rating

7.8

Reviews Sentiment

6.4

Number of Reviews

Ranking in other categories

Data Visualization (17th)

KNIME Business Hub

Ranking in Data Science Platforms

3rd

Average Rating

8.2

Reviews Sentiment

7.1

Number of Reviews

Ranking in other categories

Data Mining (1st)

Mindshare comparison

As of January 2026, in the Data Science Platforms category, the mindshare of Google Cloud Datalab is 1.4%, up from 1.0% compared to the previous year. The mindshare of KNIME Business Hub is 8.7%, down from 11.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms Market Share Distribution
Product	Market Share (%)
KNIME Business Hub	8.7%
Google Cloud Datalab	1.4%
Other	89.9%

Data Science Platforms

Featured Reviews

LijomonJose

System Architect at UST Global EspaÃ±a

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.

Read full review

DanieleGentile

BI Analyst at a photography company with 11-50 employees

Enables fast project development with efficient workflow modifications and promising features while offering modularity and reusability

KNIME is simple and allows for fast project development due to its reusability. I appreciate the ability to make improvements or modifications in existing workflows. Although I have not yet used the forecasting and customer profiling features, I find them promising. Another effective feature is the ability to use GET request objects to retrieve data from websites or APIs. This makes iterative steps easy to manage. It is more elastic and modern compared to SAP Data Services, allowing node creation and regrouping components or steps for reuse in different projects.

Read full review

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."

"Google Cloud Datalab is very customizable."

"For me, it has been a stable product."

"In MLOps, when we are designing the data pipeline, the designing of the data pipeline is easy in Google Cloud."

"The APIs are valuable."

"The infrastructure is highly reliable and efficient, contributing to a positive experience."

"It's a very powerful and simple tool to use."

"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."

"We can deploy the solution in a cluster as well."

"The ETL which helps me to collect, reformat, and load the data from multiple sources into one destination, a storage database."

"What I like the most is that it works almost out of the box with Random Forest and other Forest nodes."

"The solution is very easy to use"

"Since KNIME is a no-code platform, it is easy to work with."

"From a user-friendliness perspective, it's a great tool."

More KNIME Business Hub pros

Cons

"Even if your application is always connected to its database, the processing can be cumbersome. It shouldn't be so complicated."

"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."

"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."

"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."

"I've had some problems integrating KNIME with other solutions."

"I would like it to have data visualitation capabilities. Today I'm still creating my own data visualtions tools to present my reports."

"I would prefer to have more connectivity."

"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."

"It's difficult to provide input on the improvement area because it's more of self-learning. However, there are times when I am not able to do certain things. I don't know if it's because the solution doesn't allow me or if it's because of the lack of knowledge."

"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's documentation is not strong."

"Both RapidMiner and KNIME should be made easier to use in the field of deep learning."

More KNIME Business Hub cons

Pricing and Cost Advice

"The pricing is quite reasonable, and I would give it a rating of four out of ten."

"It is affordable for us because we have a limited number of users."

"The product is cheap."

"KNIME Business Hub is expensive for small companies."

"The client versions are mostly free, and we pay only for the KNIME server version. It's not a cheap solution."

"There is no cost for using KNIME because it is an open-source solution, but you have to pay if you need a server."

"It is free of cost. It is GNU licensed."

"It is expensive to procure the license."

"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."

"Scaling to the on-premises version requires a licensing fee per user that is a bit expensive in comparison to R, Python, and SAS."

"I use the open-source version."

More KNIME Business Hub pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

25%

Computer Software Company

10%

University

Manufacturing Company

Financial Services Firm

12%

University

Manufacturing Company

Educational Organization

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

By reviewers
Company Size	Count
Small Business	20
Midsize Enterprise	16
Large Enterprise	29

Questions from the Community

What do you like most about Google Cloud Datalab?

Google Cloud Datalab is very customizable.

See all answers

What needs improvement with Google Cloud Datalab?

See all answers

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 ...

See all answers

What do you like most about KNIME?

Since KNIME is a no-code platform, it is easy to work with.

See all answers

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.

See all answers

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...

See all answers

Comparisons

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Compared 20% of the time

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Compared 14% of the time

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Compared 9% of the time

Qlik Sense vs Google Cloud Datalab

Compared 7% of the time

Dataiku vs Google Cloud Datalab

Compared 7% of the time

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Compared 17% of the time

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Compared 12% of the time

Microsoft Azure Machine Learning Studio vs KNIME Business Hub

Compared 9% of the time

Microsoft Power BI vs KNIME Business Hub

Compared 9% of the time

Alteryx vs KNIME Business Hub

Compared 8% of the time

More KNIME Business Hub Competitors

Product Reports

Buyer's Guide

Google Cloud Datalab

January 2026

Download Google Cloud Datalab product report

Buyer's Guide

KNIME Business Hub

January 2026

Download KNIME Business Hub product report

Also Known As

No data available

KNIME Analytics Platform

Overview

Cloud Datalab is a powerful interactive tool created to explore, analyze, transform and visualize data and build machine learning models on Google Cloud Platform. It runs on Google Compute Engine and connects to multiple cloud services easily so you can focus on your data science tasks.

Google

KNIME Business Hub offers a no-code interface for data preparation and integration, making analytics and machine learning accessible. Its extensive node library allows seamless workflow execution across various data tasks.

KNIME Business Hub stands out for its user-friendly, no-code platform, promoting efficient data preparation and integration, even with Python and R. Its node library covers extensive data processes from ETL to machine learning. Community support aids users, enhancing productivity with minimal coding. However, its visualization, documentation, and interface require refinement. Larger data tasks face performance hurdles, demanding enhanced cloud connectivity and library expansions for deep learning efficiencies.

What are the most important features of KNIME Business Hub?

No-Code Interface: Simplifies data preparation without coding expertise.
Node Library: Supports diverse data tasks, including ETL and machine learning.
Python and R Integration: Seamlessly connects with popular programming languages.
Automation Capabilities: Enhances workflow productivity.
Visual Workflow Tools: Offers efficient data handling with visual aids.

What benefits and ROI can users expect from KNIME Business Hub?

Increased Productivity: Streamlined data tasks reduce development time.
Community Support: Access to extensive resources and user assistance.
Cost-Effective: Robust performance even on standard hardware.
Accessible Learning Curve: Simplicity allows easy access for educational and professional use.
Enhanced Prototyping: Ideal for decision model testing.

KNIME Business Hub finds application in data transformation, cleansing, and multi-source integration for analytics and reporting. Companies utilize it for predictive modeling, clustering, classification, machine learning, and automating workflows. Its coding-free approach suits educational and professional settings, assisting industries in data wrangling, ETLs, and prototyping decision models.

Knime

Sample Customers

Information Not Available

Infocom Corporation, Dymatrix Consulting Group, Soluzione Informatiche, MMI Agency, Estanislao Training and Solutions, Vialis AG

Buyer's Guide

Google Cloud Datalab vs. KNIME Business Hub

December 2025

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