Azure Databricks vs. Jupyter Notebook

Azure Databricks

Jupyter Notebook

Overview
Product	Rating	Most Used By	Product Summary	Starting Price
Azure Databricks	Score 8.7 out of 10	N/A	Azure Databricks is a service available on Microsoft's Azure platform and suite of products. It provides the latest versions of Apache Spark so users can integrate with open source libraries, or spin up clusters and build in a fully managed Apache Spark environment with the global scale and availability of Azure. Clusters are set up, configured, and fine-tuned to ensure reliability and performance without the need for monitoring. The solution includes autoscaling and auto-termination to improve…	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

Azure Databricks

Jupyter Notebook

Editions & Modules

No answers on this topic

Offerings

Pricing Offerings
Azure Databricks	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
	Azure Databricks	Jupyter Notebook
Considered Both Products	Azure Databricks Verified User Anonymous Chose Azure Databricks Against all the tools I have used, Azure Databricks is by far the most superior of them all! Why, you ask? The UI is modern, the features are never ending and they keep adding new features. And to quote Apple, "It just works!" Far ahead of the competition, the delta lakehouse … 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

Azure Databricks

Jupyter Notebook

Platform Connectivity

Comparison of Platform Connectivity features of Product A and Product B
	Azure Databricks 8.1 Ratings 3% below category average	Jupyter Notebook 9.0 Ratings 7% above category average
Connect to Multiple Data Sources	6.20 Ratings	10.00 Ratings
Extend Existing Data Sources	9.00 Ratings	10.00 Ratings
Automatic Data Format Detection	9.00 Ratings	8.50 Ratings
MDM Integration	8.00 Ratings	7.40 Ratings

Data Exploration

Comparison of Data Exploration features of Product A and Product B
	Azure Databricks 6.4 Ratings 27% below category average	Jupyter Notebook 7.0 Ratings 18% below category average
Visualization	5.90 Ratings	6.00 Ratings
Interactive Data Analysis	6.90 Ratings	8.00 Ratings

Data Preparation

Comparison of Data Preparation features of Product A and Product B
	Azure Databricks 8.0 Ratings 2% below category average	Jupyter Notebook 9.5 Ratings 15% above category average
Interactive Data Cleaning and Enrichment	7.00 Ratings	10.00 Ratings
Data Transformations	9.00 Ratings	10.00 Ratings
Data Encryption	9.00 Ratings	8.50 Ratings
Built-in Processors	7.10 Ratings	9.30 Ratings

Platform Data Modeling

Comparison of Platform Data Modeling features of Product A and Product B
	Azure Databricks 8.3 Ratings 1% below category average	Jupyter Notebook 9.3 Ratings 10% above category average
Multiple Model Development Languages and Tools	8.10 Ratings	10.00 Ratings
Automated Machine Learning	9.00 Ratings	9.20 Ratings
Single platform for multiple model development	8.00 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
	Azure Databricks 8.5 Ratings 0% below category average	Jupyter Notebook 10.0 Ratings 16% above category average
Flexible Model Publishing Options	8.00 Ratings	10.00 Ratings
Security, Governance, and Cost Controls	9.00 Ratings	10.00 Ratings

Best Alternatives
	Azure Databricks	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
	Azure Databricks	Jupyter Notebook
Likelihood to Recommend	9.8 (0 ratings)	10.0 (0 ratings)
Usability	8.0 (0 ratings)	10.0 (0 ratings)
Support Rating	- (0 ratings)	9.0 (0 ratings)

User Testimonials
	Azure Databricks	Jupyter Notebook
Likelihood to Recommend	Having access to all databases and tables in one place is what has helped me and my team to function better. The in built functionality/access to SQL and Python is definitely an added bonus! The icing on the cake is the ability to export your data into an Excel spreadsheet for additional analysis. If you have less to no working knowledge of SQL or Python, its better to look at alternatives. 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	Consistently great performance when dealing with huge scale data with the help of spark architecture Magic commands such as spark sql, pyspark, scala . This comes really handy in day to day work Integration with other Azure services is super smooth and robust Incentivized Pranshu Gupta Associate Data Engineer 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	Intuitive interface Ease of use Providing FAQ or QRGs 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
Usability	Based on my extensive use of Azure Databricks for the past 3.5 years, it has evolved into a beautiful amalgamation of all the data domains and needs. From a data analyst, to a data engineer, to a data scientist, it jas got them all! Being language agnostic and focused on easy to use UI based control, it is a dream to use for every Data related personnel across all experience levels! Incentivized Verified User Anonymous 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
Support Rating	No answers on this topic	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
Alternatives Considered	Against all the tools I have used, Azure Databricks is by far the most superior of them all! Why, you ask? The UI is modern, the features are never ending and they keep adding new features. And to quote Apple, "It just works!" Far ahead of the competition, the delta lakehouse platform also fares better than it counterparts of Iceberg implementation or a loosely bound Delta Lake implementation of Synapse 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
Return on Investment	The support team is amazing, they help you at every stage of the projects, from sales to delivery. On a framework level, it has had an amazing impact and has reduced the clients overall data platform costs by a staggering 65% There has been a 40% Manual work requirement on average for the clients when they move to Azure Databricks Data Platform 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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