IBM Watson Studio on Cloud Pak for Data vs. Jupyter Notebook

IBM Watson Studio on Cloud Pak for Data

Jupyter Notebook

Overview
Product	Rating	Most Used By	Product Summary	Starting Price
IBM Watson Studio	Score 10.0 out of 10	N/A	IBM Watson Studio enables users to build, run and manage AI models, and optimize decisions at scale across any cloud. IBM Watson Studio enables users can operationalize AI anywhere as part of IBM Cloud Pak® for Data, the IBM data and AI platform. The vendor states the solution simplifies AI lifecycle management and accelerates time to value with an open, flexible multicloud architecture.	N/A
Jupyter Notebook	Score 9.4 out of 10	N/A	Jupyter Notebook is an open-source web application that allows users to create and share documents containing live code, equations, visualizations and narrative text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, data visualization, and machine learning. It supports over 40 programming languages, and notebooks can be shared with others using email, Dropbox, GitHub and the Jupyter Notebook Viewer. It is used with JupyterLab, a web-based IDE for…	N/A

Pricing

IBM Watson Studio on Cloud Pak for Data

Jupyter Notebook

Editions & Modules

No answers on this topic

Offerings

Pricing Offerings
IBM Watson Studio	Jupyter Notebook
Free Trial
No	No
Free/Freemium Version
No	No
Premium Consulting/Integration Services
No	No

Entry-level Setup Fee

No setup fee

Additional Details

—

More Pricing Information

Community Pulse
	IBM Watson Studio on Cloud Pak for Data	Jupyter Notebook
Considered Both Products	IBM Watson Studio Kapil Bansal Web Developer Chose IBM Watson Studio Google Cloud may be a good place but it is not as easy to understand as IBM Watson is. Google Cloud has a lot of things and it is terrifying for a beginner. You need hours of specialization for that. On other hand, anyone can start using IBM Waston just by the following … Incentivized Helpful? Verified User Anonymous Chose IBM Watson Studio Data ingestion Batch data processing Built-in connectors to Python Incentivized Helpful? Verified User Anonymous Chose IBM Watson Studio Anaconda and Jupyter Notebook Incentivized Helpful? LR Li Rong Software Engineer Chose IBM Watson Studio AWS Sagemaker is a well-established product that supports on-demand notebooks, data pipelines, and so on, however, it also comes with the learning overhead of the whole AWS stack. It does allow per-defined models, but the benefit of using IBM Watson Studio is that users are … Incentivized Helpful? Venugopal Dontaraboyana IT Specialist Chose IBM Watson Studio Organization of data, use of data, manage the data, visualize the data is easy. Use of the environment for any project. We can use python or R or Scala in the notebook. Incentivized Helpful? Verified User Anonymous Chose IBM Watson Studio It provides better user experience. All your data on cloud and does not take up space locally. Incentivized Helpful? Verified User Anonymous Chose IBM Watson Studio I think they are very similar but IBM Watson is not good enough yet to pay for the services that I can already get from Jupyter Notebook. Incentivized Helpful? John Robert Uy President Chose IBM Watson Studio Easy to use, but still requires a lot of coding to use. There is no ranking of models used and models are not persistent, which means you have to keep running the models again every time you leave the session. The filesystem is clunky and need to keep authorizing Google Drive … Incentivized Helpful? Verified User Anonymous Chose IBM Watson Studio The main reason I personally changed over from Azure ML Studio is because it lacked any support for significant custom modelling with packages and services such as TensorFlow, scikit-learn, Microsoft Cognitive Toolkit and Spark ML. IBM Watson Studio provides these services and … Incentivized Helpful? NARESH SAMPARA Research Associate Chose IBM Watson Studio IBM offers a deep neural network training workflow, with a flow editor interface similar to the one used in Azure ML Studio. However, the custom build modeling in IBM has notebooks such as Jupiter to program models manually using popular frameworks like TensorFlow, … Incentivized Helpful? Verified User Anonymous Chose IBM Watson Studio As it offers more features and can be used for several applications like AI,ML,DS etc., Incentivized Helpful? MW Michael Weaver Logistic Assistance Representave (LAR) Chose IBM Watson Studio With my experience on Jupyter Notebook I think both are good and currently more comfortable with Watson Studio product. With Jupyter it's open source (free) is always good. "Lots of languages (50), data visualization with Seaborn, work with the building blocks in a flexible and … Incentivized Helpful? Verified User Anonymous Chose IBM Watson Studio We didn’t evaluate other products but we liked what we saw in Watson Studio. Incentivized Helpful? Christopher Penn Co-Founder and Chief Innovator Chose IBM Watson Studio As an IBM Business Partner, we are financially incentivized to recommend and deploy IBM solutions where it makes sense to do so for the customer. Against other solutions, few have the governance and security that IBM offers, which is essential for any kind of work in highly … Incentivized Helpful? ashish devassy Manager Chose IBM Watson Studio We did not use any other one so this would be hard for me to answer. Incentivized Helpful? Verified User Anonymous Chose IBM Watson Studio They are close, but I feel Alteryx is more of an enhanced Jupyter capability, whereas WS is more of an enterprise solution for multiple teams Incentivized Helpful? Verified User Anonymous Chose IBM Watson Studio Not applicable Incentivized Helpful? Van West Chief Strategy Officer Chose IBM Watson Studio Less satisfied with Watson and lack of support. Incentivized Helpful? Verified User Anonymous Chose IBM Watson Studio I am excited with the roadmap of Watson Studio incorporating SPSS Modeler in the offerings. Incentivized Helpful? Isaiah King Founding Member Chose IBM Watson Studio Watson Studio was our choice in data management because its "all-in-one" packaging. Watson studio also stood out to us because it was more affordable and free for our organization to try out. We also greatly value the open source ecosystem Watson Studio has fostered. Incentivized Helpful? Dr. George Ng Lecturer (Software and Information Technology Council) Chose IBM Watson Studio AWS Sagemaker is new, and I personally think it's better than sliced bread. There's very little set up to do. Watson Studio needs to up its game against Sagemaker. Incentivized Helpful? Verified User Anonymous Chose IBM Watson Studio AWS stacks up very favourably against Watson Studio, and in fact this is what the customer ultimately chose over Watson Studio after an evaluation period due to the sophistication, maturity, security, and capabilities of the AWS components. The downsides of AWS are having to … Incentivized Helpful? Sebastian Ferro Consultant Sr. Chose IBM Watson Studio Watson Studio offers more capabilities and diversity in tools and services. Incentivized Helpful? Verified User Anonymous Chose IBM Watson Studio The learning curve for DSX is smaller compared to other tools. The data science user base often has preferred tools that they have used previously which are often not DSX which makes adoption of DSX by trained data scientists harder than new users. Incentivized Helpful? Andrea Bardone consultant Chose IBM Watson Studio IBM DSx is more comprehensive and easy to use, IBM Data science experience has many connectors to the data source and guarantees the portability with your old projects. Incentivized Helpful?	Jupyter Notebook Verified User Anonymous Chose Jupyter Notebook As a beginner I tried all of them but finally due to simple and user friendly interface I opted it. I also tried visual basic which is also good platform with versatility, however for basic need it is the best. Incentivized Helpful? Verified User Anonymous Chose Jupyter Notebook Jupyter is very easy to understand and easy to use. And can also be used by a student, freelancer, small industries, big industries. Jupyter also provides you a tool to work with machine learning and artificial intelligence. Incentivized Helpful? Verified User Anonymous Chose Jupyter Notebook Negligible or no cost, Highly efficient, effective, scalable , hasslefree Incentivized Helpful? Shivam Rai Senior Implementation Services Assistant Chose Jupyter Notebook Jupyter Notebook is very attractive platform for new developers to code and to learn programming and perform tasks as compared to other IDE. It has very well and easy visualization, interactive programming and sharing the live code and slideshow is very easy as compare to … Incentivized Helpful? RL Rita Lo Chose Jupyter Notebook Jupyter is still the most well known and widely used platform I've seen. Using it over other competition like Zeppelin simply because of its availability, and my familiarity with its functionality. Incentivized Helpful? Lindsay Veazey Senior Data Scientist Chose Jupyter Notebook Jupyter Notebook is unique in that it offers a flexible, lightweight, easy-to-replicate way of organizing your code in a visually intuitive fashion that can be exported in a number of formats. I've found that the broad functionalities available within the notebooks suit a lot … Incentivized Helpful? Ejaz Hussain Senior Analyst Chose Jupyter Notebook Well, so far Jupyter Notebook has been the better tool for me. It gives us more freedom & has more ability to train ML models & do the data visualization more efficiently. It's easier to operate & has a very simple-to-understand UI & with the support for taking data from … Incentivized Helpful? RV Rounak Verma Data Analyst Chose Jupyter Notebook I have used PyCharm as well as Jupyter Notebook and for me, Jupyter wins almost every time. I really like its user-friend interface for someone who is new to python programming. The ability to run a big chunk of code part by part is a big game-changer for me. One thing I would … Incentivized Helpful? Hemant Jajoo Machine Learning Intern Chose Jupyter Notebook It should have cleaner support for multi-environment setup and should also increase the amount of features. Moreover, more support should be present for other programming languages. It should also have the option to set a specific location that opens up whenever I run command … Incentivized Helpful? AJ Ayushi Jain Technical Specialist Chose Jupyter Notebook Jupyter is easier to handle and user friendly. We have free access to it and its cell by cell executing feature is amazing. Incentivized Helpful? Verified User Anonymous Chose Jupyter Notebook Jupyter Notebook has a nicer interface than RStudio in our opinion and since most of our group is familiar with Jupyter Notebook it has made it a default choice. Overall the interactive programming as well as the easy visualizations, model deployment, and markdown made Jupyter … Incentivized Helpful? Verified User Anonymous Chose Jupyter Notebook Jupyter Notebook is the core feature extended on by many commercial alternatives. The commercial alternatives have more feature integration with the rest of their portfolio. RStudio is another competitor for interactive and literate programming. Incentivized Helpful? Arpit Ranka Graduate Student Chose Jupyter Notebook haven't actually explored as I decided to use it on a friend 's recommendation. Incentivized Helpful? Verified User Anonymous Chose Jupyter Notebook An interesting thing is that Jupyter Notebook is run on browser environments which may or may not be a positive feature according to cases. VS Code on [the] other hand doesn't use any interface and can run Jupyter Notebooks too. Sometimes my browser consumes too much RAM due to … Incentivized Helpful? Irene Rodríguez Alegre Data Scientist - HF Radar Chose Jupyter Notebook It was great to import and export data and plots using Jupyter Incentivized Helpful? RK Rahul Kapoor Software Engineer Chose Jupyter Notebook With Jupyter Notebook besides doing data analysis and performing complex visualizations you can also write machine learning algorithms with a long list of libraries that it supports. You can make better predictions, observations etc. with it which can help you achieve better … Incentivized Helpful? JJ Jewon Ju Data Analyst Chose Jupyter Notebook I like Jupyter Notebook over the other two because it keeps my work more organized. It helps me to structure my workflow and the ability to run commands in chunks keeps me from being confused when coming back to the work after some time. Incentivized Helpful? YX Yaxian Xie BIE Chose Jupyter Notebook I selected Jupyter Notebook because this is better integrated with the existing production systems than optional tools (for example, R). It is also commonly used tool within the scientist community. Incentivized Helpful? Verified User Anonymous Chose Jupyter Notebook When I tried Zeppelin in 2017, it was still in initial versions, Jupyter was way ahead as of then. Zeppelin had limitations and I wasn't confident of it making progress as much as Jupyter. Incentivized Helpful?

Features

IBM Watson Studio on Cloud Pak for Data

Jupyter Notebook

Platform Connectivity

Comparison of Platform Connectivity features of Product A and Product B
	IBM Watson Studio on Cloud Pak for Data 8.1 Ratings 3% below category average	Jupyter Notebook 9.0 Ratings 7% above category average
Connect to Multiple Data Sources	8.00 Ratings	10.00 Ratings
Extend Existing Data Sources	8.00 Ratings	10.00 Ratings
Automatic Data Format Detection	10.00 Ratings	8.50 Ratings
MDM Integration	6.40 Ratings	7.40 Ratings

Data Exploration

Comparison of Data Exploration features of Product A and Product B
	IBM Watson Studio on Cloud Pak for Data 10.0 Ratings 18% above category average	Jupyter Notebook 7.0 Ratings 18% below category average
Visualization	10.00 Ratings	6.00 Ratings
Interactive Data Analysis	10.00 Ratings	8.00 Ratings

Data Preparation

Comparison of Data Preparation features of Product A and Product B
	IBM Watson Studio on Cloud Pak for Data 9.5 Ratings 15% above category average	Jupyter Notebook 9.5 Ratings 15% above category average
Interactive Data Cleaning and Enrichment	10.00 Ratings	10.00 Ratings
Data Transformations	10.00 Ratings	10.00 Ratings
Data Encryption	8.00 Ratings	8.50 Ratings
Built-in Processors	10.00 Ratings	9.30 Ratings

Platform Data Modeling

Comparison of Platform Data Modeling features of Product A and Product B
	IBM Watson Studio on Cloud Pak for Data 9.5 Ratings 13% above category average	Jupyter Notebook 9.3 Ratings 10% above category average
Multiple Model Development Languages and Tools	10.00 Ratings	10.00 Ratings
Automated Machine Learning	10.00 Ratings	9.20 Ratings
Single platform for multiple model development	10.00 Ratings	10.00 Ratings
Self-Service Model Delivery	8.00 Ratings	8.00 Ratings

Model Deployment

Comparison of Model Deployment features of Product A and Product B
	IBM Watson Studio on Cloud Pak for Data 8.0 Ratings 6% below category average	Jupyter Notebook 10.0 Ratings 16% above category average
Flexible Model Publishing Options	9.00 Ratings	10.00 Ratings
Security, Governance, and Cost Controls	7.00 Ratings	10.00 Ratings

Best Alternatives
	IBM Watson Studio on Cloud Pak for Data	Jupyter Notebook
Small Businesses	Jupyter Notebook Score 9.4 out of 10	IBM Watson Studio Score 10.0 out of 10
Medium-sized Companies	Posit Score 10.0 out of 10	Posit Score 10.0 out of 10
Enterprises	Posit Score 10.0 out of 10	Posit Score 10.0 out of 10
All Alternatives	View all alternatives	View all alternatives

User Ratings
	IBM Watson Studio on Cloud Pak for Data	Jupyter Notebook
Likelihood to Recommend	8.0 (0 ratings)	10.0 (0 ratings)
Likelihood to Renew	8.2 (0 ratings)	- (0 ratings)
Usability	9.6 (0 ratings)	10.0 (0 ratings)
Availability	8.2 (0 ratings)	- (0 ratings)
Performance	8.2 (0 ratings)	- (0 ratings)
Support Rating	8.2 (0 ratings)	9.0 (0 ratings)
In-Person Training	8.2 (0 ratings)	- (0 ratings)
Online Training	8.2 (0 ratings)	- (0 ratings)
Implementation Rating	7.3 (0 ratings)	- (0 ratings)
Product Scalability	8.2 (0 ratings)	- (0 ratings)
Vendor post-sale	7.3 (0 ratings)	- (0 ratings)
Vendor pre-sale	8.2 (0 ratings)	- (0 ratings)

User Testimonials
	IBM Watson Studio on Cloud Pak for Data	Jupyter Notebook
Likelihood to Recommend	It has a lot of features that are good for teams working on large-scale projects and continuously developing and reiterating their data project models. Really helpful when dealing with large data. It is a kind of one-stop solution for all data science tasks like visualization, cleaning, analyzing data, and developing models but small teams might find a lot of features unuseful. Incentivized Verified User Anonymous Read full review	I would rate it 9/10 while recommending Jupyter Notebook as it offers me a wide range of functionality to operate. It is very well suited for someone who is new to python programming as the user interface helps you build code line by line. I personally have written multiple programs in Python using Jupyter Notebook as it helps me organize long code by breaking it in a structure. Also the ability to write comments using '#' helps a lot to a reader understand the code. Incentivized RV Rounak Verma Data Analyst Read full review
Pros	Integration of IBM Watson APIs such as speech to text, image recognition, personality insights, etc. SPSS modeler and neural network model provide no-code environments for data scientists to build pipelines quickly. Enforced best-practices set up POCs for deployment in production with a minimum of re-work. Estimator validation lets data scientists test and prove different models. Incentivized Christopher Penn Co-Founder and Chief Innovator Read full review	Coding and error correction line by line Simple and Effectiveness Easy to use for visualisation and presentation of code Could be used at any place any time without hassle Incentivized Verified User Anonymous Read full review
Cons	The cost is steep and so only companies with resources can afford it It will be nice to have Chinese versions so that Chinese engineers can also use it easily It takes a while to learn how to input different kinds of skin defects for detection Incentivized Verified User Anonymous Read full review	Need more Hotkeys for creating a beautiful notebook. Sometimes we need to download other plugins which messes [with] its default settings. Not as powerful as IDE, which sometimes makes [the] job difficult and allows duplicate code as it get confusing when the number of lines increases. Need a feature where [an] error comes if duplicate code is found or [if a] developer tries the same function name. Incentivized Verified User Anonymous Read full review
Likelihood to Renew	because we find out that DSX results have improved our approach to the whole subject (data, models, procedures) Incentivized Davide Tognon Engineering Technician Read full review	No answers on this topic
Usability	The UI flawlessly merges this offering by providing a neat, minimal, responsive interface Incentivized Isaiah King Founding Member Read full review	Jupyter is highly simplistic. It took me about 5 mins to install and create my first "hello world" without having to look for help. The UI has minimalist options and is quite intuitive for anyone to become a pro in no time. The lightweight nature makes it even more likeable. Incentivized Verified User Anonymous Read full review
Reliability and Availability	From time to time there are services unavailable, but we have been always informed before and they got back to work sooner than expected Incentivized Davide Tognon Engineering Technician Read full review	No answers on this topic
Performance	Never had slow response even on our very busy network Incentivized Davide Tognon Engineering Technician Read full review	No answers on this topic
Support Rating	I received answers mostly at once and got answered even further my question: they gave me interesting points of view and suggestion for deepening in the learning path Incentivized Davide Tognon Engineering Technician Read full review	I haven't had a need to contact support. However, all required help is out there in public forums. Incentivized Verified User Anonymous Read full review
In-Person Training	The trainers on the job are very smart with solutions and very able in teaching Incentivized Davide Tognon Engineering Technician Read full review	No answers on this topic
Online Training	The Platform is very handy and suggests further steps according my previous interests Incentivized Davide Tognon Engineering Technician Read full review	No answers on this topic
Implementation Rating	It surprised us with unpredictable case of use and brand new points of view Incentivized Davide Tognon Engineering Technician Read full review	No answers on this topic
Alternatives Considered	The main reason I personally changed over from Azure ML Studio is because it lacked any support for significant custom modelling with packages and services such as TensorFlow, scikit-learn, Microsoft Cognitive Toolkit and Spark ML. IBM Watson Studio provides these services and does so in a well integrated and easy to use fashion making it a preferable service over the other services that I have personally used. Incentivized Verified User Anonymous Read full review	Jupyter Notebook is unique in that it offers a flexible, lightweight, easy-to-replicate way of organizing your code in a visually intuitive fashion that can be exported in a number of formats. I've found that the broad functionalities available within the notebooks suit a lot of needs I have for EDA, modeling, and data export that makes other software products fairly redundant. Incentivized Lindsay Veazey Senior Data Scientist Read full review
Scalability	It helped us in getting from 0 to DSX without getting lost Incentivized Davide Tognon Engineering Technician Read full review	No answers on this topic
Return on Investment	Could instantly show data driven insights to drive 20% incremental revenue over existing results Still don't have a real use case for unstructured data like twitter feed Some of the insights around user actions have driven new projects to automate mundane tasks Incentivized Verified User Anonymous Read full review	Positive impact: flexible implementation on any OS, for many common software languages Positive impact: straightforward duplication for adaptation of workflows for other projects Negative impact: sometimes encourages pigeonholing of data science work into notebooks versus extending code capability into software integration Incentivized Lindsay Veazey Senior Data Scientist Read full review
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