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Anaconda Business vs Databricks vs KNIME Business 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
6.2
Anaconda Business enhances efficiency and decision-making, leading to reduced costs and improved project delivery for significant ROI.
Sentiment score
6.5
Databricks reduces costs and boosts efficiency, yet some users struggle to realize financial gains despite improved productivity.
Sentiment score
6.2
KNIME Business Hub offers high ROI with low cost, easy use, and productivity boosts, especially for Azure or AWS users.
Everyone being able to work smoothly without unnecessary delays.
tester at a tech vendor with 10,001+ employees
I have seen a return on investment; specifically, when we talk about efficiency, it's both time-saving and money-saving.
Product managaer at Zidio development
I have seen a return on investment with time saved by 50% and less downtime, allowing the team to deliver projects faster with fewer errors.
Analyst at Tata consultancy services
This reduction in both time and money resulted in real-time impact and significant cost savings.
Consultant at Nice Software Solutions
For a lot of different tasks, including machine learning, it is a nice solution.
Senior Data Engineer at a logistics company with 51-200 employees
When it comes to big data processing, I prefer Databricks over other solutions.
Head CEO at bizmetric
 

Customer Service

Sentiment score
5.4
Anaconda Business offers prompt, helpful customer support, with users relying more on documentation and community resources like Stack Overflow.
Sentiment score
6.9
Databricks support is professional and responsive, with users appreciating efficient issue resolution and effective assistance despite occasional delays.
Sentiment score
6.7
KNIME Business Hub's strong community support and quick forum responses earn praise, despite limited official support and documentation gaps.
Anaconda Business customer support is very active with a quick response time.
System Engineer at a tech vendor with 10,001+ employees
Overall, support was reliable when we needed it, just not super-fast every single time.
tester at a tech vendor with 10,001+ employees
The customer support for Anaconda Business provides a better approach.
Product managaer at Zidio development
Whenever we reach out, they respond promptly.
Senior Data Engineer at a logistics company with 51-200 employees
As of now, we are raising issues and they are providing solutions without any problems.
Data Platform Architect at KELLANOVA
I rate the technical support as fine because they have levels of technical support available, especially partners who get really good support from Databricks on new features.
Data Engineer at CRAFT Tech
While they cannot always provide immediate answers, they are generally efficient and simplify tasks, especially in the initial phase of learning KNIME.
BI Analyst at a photography company with 11-50 employees
My mark for technical support for KNIME Business Hub is about a 7, as most of the support is in the community, and it is quite good because it is open source.
Senior Consultant at a tech vendor with 10,001+ employees
 

Scalability Issues

Sentiment score
6.7
Anaconda Business efficiently supports scalability, seamless expansion, and smooth performance for growing projects and teams in organizations.
Sentiment score
7.4
Databricks is praised for scalable, cost-effective cloud compatibility, efficient data handling, and seamless integration with Azure and AWS.
Sentiment score
6.8
KNIME Business Hub is scalable for moderate data but faces RAM limitations with large datasets on desktops.
As more environments or users get added, it still runs smoothly without major slowdowns.
tester at a tech vendor with 10,001+ employees
Anaconda Business scales very well because it is built around centralized environment and package management.
System Engineer at a tech vendor with 10,001+ employees
Anaconda does not have scalability restrictions as it depends on the type of machine running it.
VP Product at Medint
The sky's the limit with Databricks.
Governance And Engagement Lead
The patches have sometimes caused issues leading to our jobs being paused for about six hours.
Senior Data Engineer at a logistics company with 51-200 employees
Databricks is an easily scalable platform.
Data Platform Architect at KELLANOVA
 

Stability Issues

Sentiment score
7.4
Anaconda Business is stable and efficient, offering reduced setup time and performance improvements despite minor memory and update issues.
Sentiment score
7.6
Databricks is generally stable and reliable, with occasional glitches, handling large data sets effectively according to users.
Sentiment score
7.6
KNIME Business Hub is reliable with some crashes; strong hardware and active community support ensure high user satisfaction.
Earlier, setting up or troubleshooting conflicts could take anywhere from thirty minutes to an hour, but now most setups just work.
tester at a tech vendor with 10,001+ employees
Anaconda Business is stable to an extent, but it sometimes crashes on systems with insufficient RAM.
Software Engineer at a financial services firm with 51-200 employees
They release patches that sometimes break our code.
Senior Data Engineer at a logistics company with 51-200 employees
Although it is too early to definitively state the platform's stability, we have not encountered any issues so far.
Data Platform Architect at KELLANOVA
Databricks is definitely a very stable product and reliable.
Data Engineer at a tech vendor with 1,001-5,000 employees
For now, KNIME Business Hub is excellent for me and for our team.
Co Founder & Chief Data Officer Cdo at NTT DATA
From 1 to 10, I would rate the stability of KNIME Business Hub quite good, around an 8 or 9.
Senior Consultant at a tech vendor with 10,001+ employees
 

Room For Improvement

Anaconda Business needs OS compatibility updates, user interface improvements, better documentation, and enhanced performance, stability, and functionality.
Databricks requires better visualization, integration, pricing, user experience, scalability, and documentation to enhance functionality and user adaptation.
KNIME Business Hub needs improvements in algorithms, data handling, UI, integration, performance, documentation, and training for better user experience.
It would also be nice to have clearer error messages when something fails, so it is easier to understand what went wrong without digging too much.
tester at a tech vendor with 10,001+ employees
They should enhance the security point of view; it's good, but it needs some more advanced features.
Product managaer at Zidio development
The pricing should be a little lower for a single person to use, as it might be affordable for an organization, but for my single use, it is difficult.
Product Engineer at a tech vendor with 10,001+ employees
Adjusting features like worker nodes and node utilization during cluster creation could mitigate these failures.
Data Engineer at a engineering company with 1,001-5,000 employees
We prefer using a small to mid-sized cluster for many jobs to keep costs low, but this sometimes doesn't support our operations properly.
Senior Data Engineer at a logistics company with 51-200 employees
We use MLflow for managing MLOps, however, further improvement would be beneficial, especially for large language models and related tools.
Solution Architect at Mercedes-Benz AG
I would like to see additional functions in KNIME Business Hub that can connect to generative AI, allowing users to describe the workflow for easier workflow generation and creation.
Senior Consultant at a tech vendor with 10,001+ employees
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.
Co Founder & Chief Data Officer Cdo at NTT DATA
For graphics, the interface is a little confusing.
Student at ISCTE - INSTITUTO UNIVERSITÁRIO DE LISBOA
 

Setup Cost

Anaconda Business offers reasonable costs and broad compatibility, despite additional hardware expenses, maintaining satisfaction with free tool access.
Databricks offers competitive, flexible pay-per-use pricing, but costs vary by usage, often higher than open-source alternatives.
KNIME Business Hub offers a cost-effective, open-source desktop version for small teams, with scalable server options for enterprises.
Anaconda is an open-source tool, so I do not pay anything for it.
VP Product at Medint
My experience with pricing, setup cost, and licensing is that it is a little costly, but it is useful.
Automation Test Engineer at Tata Consultancy services Limited
My experience with pricing, setup cost, and licensing indicates that it is a bit costly, but it is useful.
Analyst at Tata consultancy services
It is not a cheap solution.
Data Platform Architect at KELLANOVA
I believe that in terms of credits for Databricks, we're spending between £15,000 and £20,000 a month.
Governance And Engagement Lead
 

Valuable Features

Anaconda Business enhances productivity with centralized management, security, multi-language support, and seamless Python and R integration.
Databricks offers scalable analytics with powerful machine learning, seamless cloud integration, and efficient data governance for rapid data processing.
KNIME Business Hub streamlines complex tasks with a user-friendly interface, extensions, and support for analytics and automation.
Anaconda Business has positively impacted my organization because, when discussing the security point of view, it's exceptional; when comparing it to other solutions, Anaconda Business is superior.
Product managaer at Zidio development
We find the advanced security, governance, and collaborative features for organizations using Python and R particularly useful.
Product Engineer at a tech vendor with 10,001+ employees
Anaconda Business positively impacts our organization by protecting us from compliance and security risks while keeping the environment consistent, allowing our team to focus on insight and innovation instead of worrying about setups, security, and software issues.
Analyst at Tata consultancy services
Databricks' capability to process data in parallel enhances data processing speed.
Data Engineer at a engineering company with 1,001-5,000 employees
The platform allows us to leverage cloud advantages effectively, enhancing our AI and ML projects.
Data Platform Architect at KELLANOVA
The Unity Catalog is for data governance, and the Delta Lake is to build the lakehouse.
Data Engineer at CRAFT Tech
KNIME is more intuitive and easier to use, which is the principal advantage.
Student at ISCTE - INSTITUTO UNIVERSITÁRIO DE LISBOA
KNIME is simple and allows for fast project development due to its reusability.
BI Analyst at a photography company with 11-50 employees
It is very important that I have the workflow automation integrated with Python nodes.
Co Founder & Chief Data Officer Cdo at NTT DATA
 

Mindshare comparison

As of April 2026, in the Data Science Platforms category, the mindshare of Anaconda Business is 2.3%, up from 2.1% compared to the previous year. The mindshare of Databricks is 9.3%, down from 18.5% compared to the previous year. The mindshare of KNIME Business Hub is 6.8%, down from 11.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms Mindshare Distribution
ProductMindshare (%)
Databricks9.3%
KNIME Business Hub6.8%
Anaconda Business2.3%
Other81.6%
Data Science Platforms
 

Featured Reviews

reviewer2775498 - PeerSpot reviewer
tester at a tech vendor with 10,001+ employees
Isolate environments and switch package versions efficiently for smoother testing workflows
Overall, it works well, but there are a few things that could be better. Sometimes the environment creation or package installation feels a bit slow, especially with bigger libraries. Another thing I would appreciate is a cleaner, more intuitive interface for managing environments. It works, but a smoother UI could make the workflow faster. It would also be nice to have clearer error messages when something fails, so it is easier to understand what went wrong without digging too much. The documentation could be a bit clearer, especially for troubleshooting specific errors or setup issues. Sometimes I need to search extensively to find the exact steps. Also, having quicker or more detailed support responses would help when something unexpected comes up. These are not major problems, but improving them would definitely make the overall experience smoother. One small improvement I would add is smoother integration with IDEs. It works fine right now, but having even tighter or more automated syncing with tools such as VS Code or PyCharm would make the workflow faster. Perhaps also a few more built-in examples or quick-start guides for common setups would be helpful. Nothing major, just things that would make the experience even more user-friendly.
SimonRobinson - PeerSpot reviewer
Governance And Engagement Lead
Improved data governance has enabled sensitive data tracking but cost management still needs work
I believe we could improve Databricks integration with cloud service providers. The impact of our current integration has not been particularly good, and it's becoming very expensive for us. The inefficiencies in our implementation, such as not shutting down warehouses when they're not in use or reserving the right number of credits, have led to increased costs. We made several beginner mistakes, such as not taking advantage of incremental loading and running overly complicated queries all the time. We should be using ETL tools to help us instead of doing it directly in Databricks. We need more experienced professionals to manage Databricks effectively, as it's not as forgiving as other platforms such as Snowflake. I think introducing customer repositories would facilitate easier implementation with Databricks.
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.
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Top Industries

By visitors reading reviews
Financial Services Firm
14%
University
12%
Manufacturing Company
8%
Computer Software Company
7%
Financial Services Firm
18%
Manufacturing Company
9%
Computer Software Company
8%
Healthcare Company
6%
Financial Services Firm
12%
Manufacturing Company
9%
University
8%
Educational Organization
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business12
Midsize Enterprise2
Large Enterprise19
By reviewers
Company SizeCount
Small Business27
Midsize Enterprise12
Large Enterprise56
By reviewers
Company SizeCount
Small Business20
Midsize Enterprise16
Large Enterprise31
 

Questions from the Community

What do you like most about Anaconda?
The tool's most valuable feature is its cloud-based nature, allowing accessibility from anywhere. Additionally, using...
What is your experience regarding pricing and costs for Anaconda?
My experience with pricing, setup cost, and licensing is that it is a little costly, but it is useful.
What needs improvement with Anaconda?
I believe Anaconda Business can be improved in terms of performance and speed, particularly regarding the installatio...
Which do you prefer - Databricks or Azure Machine Learning Studio?
Databricks gives you the option of working with several different languages, such as SQL, R, Scala, Apache Spark, or ...
How would you compare Databricks vs Amazon SageMaker?
We researched AWS SageMaker, but in the end, we chose Databricks. Databricks is a Unified Analytics Platform designe...
Which would you choose - Databricks or Azure Stream Analytics?
Databricks is an easy-to-set-up and versatile tool for data management, analysis, and business analytics. For analyti...
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 ver...
 

Also Known As

No data available
Databricks Unified Analytics, Databricks Unified Analytics Platform, Redash
KNIME Analytics Platform
 

Overview

 

Sample Customers

LinkedIn, NASA, Boeing, JP Morgan, Recursion Pharmaceuticals, DARPA, Microsoft, Amazon, HP, Cisco, Thomson Reuters, IBM, Bridgestone
Elsevier, MyFitnessPal, Sharethrough, Automatic Labs, Celtra, Radius Intelligence, Yesware
Infocom Corporation, Dymatrix Consulting Group, Soluzione Informatiche, MMI Agency, Estanislao Training and Solutions, Vialis AG
Find out what your peers are saying about Databricks, Amazon Web Services (AWS), Knime and others in Data Science Platforms. Updated: March 2026.
885,837 professionals have used our research since 2012.