Apache Hadoop vs. Jupyter Notebook

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Hadoop
Score 7.3 out of 10
N/A
Hadoop is an open source software from Apache, supporting distributed processing and data storage. Hadoop is popular for its scalability, reliability, and functionality available across commoditized hardware.N/A
Jupyter Notebook
Score 8.7 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
Apache HadoopJupyter Notebook
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
HadoopJupyter Notebook
Free Trial
NoNo
Free/Freemium Version
YesNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Features
Apache HadoopJupyter Notebook
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
Apache Hadoop
-
Ratings
Jupyter Notebook
8.5
21 Ratings
1% above category average
Connect to Multiple Data Sources00 Ratings9.021 Ratings
Extend Existing Data Sources00 Ratings9.220 Ratings
Automatic Data Format Detection00 Ratings8.514 Ratings
MDM Integration00 Ratings7.415 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
Apache Hadoop
-
Ratings
Jupyter Notebook
9.6
21 Ratings
13% above category average
Visualization00 Ratings9.621 Ratings
Interactive Data Analysis00 Ratings9.621 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
Apache Hadoop
-
Ratings
Jupyter Notebook
9.0
21 Ratings
9% above category average
Interactive Data Cleaning and Enrichment00 Ratings9.320 Ratings
Data Transformations00 Ratings8.921 Ratings
Data Encryption00 Ratings8.514 Ratings
Built-in Processors00 Ratings9.314 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
Apache Hadoop
-
Ratings
Jupyter Notebook
8.9
21 Ratings
5% above category average
Multiple Model Development Languages and Tools00 Ratings9.020 Ratings
Automated Machine Learning00 Ratings9.218 Ratings
Single platform for multiple model development00 Ratings9.221 Ratings
Self-Service Model Delivery00 Ratings8.020 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
Apache Hadoop
-
Ratings
Jupyter Notebook
8.8
19 Ratings
3% above category average
Flexible Model Publishing Options00 Ratings8.819 Ratings
Security, Governance, and Cost Controls00 Ratings8.718 Ratings
Best Alternatives
Apache HadoopJupyter Notebook
Small Businesses

No answers on this topic

IBM SPSS Modeler
IBM SPSS Modeler
Score 7.8 out of 10
Medium-sized Companies
Cloudera Manager
Cloudera Manager
Score 9.7 out of 10
Mathematica
Mathematica
Score 8.3 out of 10
Enterprises
IBM Analytics Engine
IBM Analytics Engine
Score 8.8 out of 10
IBM SPSS Modeler
IBM SPSS Modeler
Score 7.8 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Apache HadoopJupyter Notebook
Likelihood to Recommend
8.9
(36 ratings)
8.4
(22 ratings)
Likelihood to Renew
9.6
(8 ratings)
-
(0 ratings)
Usability
8.5
(5 ratings)
10.0
(1 ratings)
Performance
8.0
(1 ratings)
-
(0 ratings)
Support Rating
7.5
(3 ratings)
9.0
(1 ratings)
Online Training
6.1
(2 ratings)
-
(0 ratings)
User Testimonials
Apache HadoopJupyter Notebook
Likelihood to Recommend
Apache
Altogether, I want to say that Apache Hadoop is well-suited to a larger and unstructured data flow like an aggregation of web traffic or even advertising. I think Apache Hadoop is great when you literally have petabytes of data that need to be stored and processed on an ongoing basis. Also, I would recommend that the software should be supplemented with a faster and interactive database for a better querying service. Lastly, it's very cost-effective so it is good to give it a shot before coming to any conclusion.
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Open Source
I've created a number of daisy chain notebooks for different workflows, and every time, I create my workflows with other users in mind. Jupiter Notebook makes it very easy for me to outline my thought process in as granular a way as I want without using innumerable small. inline comments.
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Pros
Apache
  • Handles large amounts of unstructured data well, for business level purposes
  • Is a good catchall because of this design, i.e. what does not fit into our vertical tables fits here.
  • Decent for large ETL pipelines and logging free-for-alls because of this, also.
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Open Source
  • Simple and elegant code writing ability. Easier to understand the code that way.
  • The ability to see the output after each step.
  • The ability to use ton of library functions in Python.
  • Easy-user friendly interface.
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Cons
Apache
  • Less organizational support system. Bugs need to be fixed and outside help take a long time to push updates
  • Not for small data sets
  • Data security needs to be ramped up
  • Failure in NameNode has no replication which takes a lot of time to recover
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Open Source
  • 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.
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Likelihood to Renew
Apache
Hadoop is organization-independent and can be used for various purposes ranging from archiving to reporting and can make use of economic, commodity hardware. There is also a lot of saving in terms of licensing costs - since most of the Hadoop ecosystem is available as open-source and is free
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Open Source
No answers on this topic
Usability
Apache
Great! Hadoop has an easy to use interface that mimics most other data warehouses. You can access your data via SQL and have it display in a terminal before exporting it to your business intelligence platform of choice. Of course, for smaller data sets, you can also export it to Microsoft Excel.
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Open Source
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.
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Support Rating
Apache
We went with a third party for support, i.e., consultant. Had we gone with Azure or Cloudera, we would have obtained support directly from the vendor. my rating is more on the third party we selected and doesn't reflect the overall support available for Hadoop. I think we could have done better in our selection process, however, we were trying to use an already approved vendor within our organization. There is plenty of self-help available for Hadoop online.
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Open Source
I haven't had a need to contact support. However, all required help is out there in public forums.
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Online Training
Apache
Hadoop is a complex topic and best suited for classrom training. Online training are a waste of time and money.
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Open Source
No answers on this topic
Alternatives Considered
Apache
Not used any other product than Hadoop and I don't think our company will switch to any other product, as Hadoop is providing excellent results. Our company is growing rapidly, Hadoop helps to keep up our performance and meet customer expectations. We also use HDFS which provides very high bandwidth to support MapReduce workloads.
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Open Source
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 business decisions and save cost to the company. It stacks up better as we know Python is more widely used than R in the industry and can be learnt easily. Unlike PyCharm jupyter notebooks can be used to make documentations and exported in a variety of formats.
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Return on Investment
Apache
  • There are many advantages of Hadoop as first it has made the management and processing of extremely colossal data very easy and has simplified the lives of so many people including me.
  • Hadoop is quite interesting due to its new and improved features plus innovative functions.
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Open Source
  • 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
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ScreenShots