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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    Jupyter Notebook

    Score8.6 out of 10
    N/AJupyter 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

    Sigma

    Score8.4 out of 10
    N/ASigma Computing headquartered in San Francisco provides a suite of data services such as code free data modeling, data search and explorating, and related BI and data visualization services.N/A
    Pricing
    Jupyter NotebookSigma
    Editions & Modules
    No answers on this topic
    No answers on this topic
    Offerings
    Pricing Offerings
    Jupyter NotebookSigma
    Free Trial
    NoYes
    Free/Freemium Version
    NoNo
    Premium Consulting/Integration Services
    NoNo
    Entry-level Setup FeeNo setup feeOptional
    Additional Details—Contact us for pricing.
    More Pricing Information
    Community Pulse
    Jupyter NotebookSigma
    Considered Both Products
    Open Source
    No answer on this topic
    Sigma Computing
    Chose Sigma
    Jupyter is better for ad-hoc analysis.
    Incentivized
    Chose Sigma
    Sigma is my least favorite BI tool I have used. Its unintuitive, takes longer to develop on, and has very limited functionality to re-use work (ie scripting, copying to a new project).
    Incentivized
    Chose Sigma
    Most legacy BI tools are just that--built in and for a time that has mostly passed. Each tool seems to have strengths in certain areas, but can be overly complex to take full advantage of and can make some of the most basic tasks difficult to discover and use. Sigma Computing …
    Incentivized
    Key User Insights
    Would buy again
    100%
    Would buy again
    23 Answers
    94%
    Would buy again
    118 Answers
    Delivers good value for the price
    100%
    Delivers good value for the price
    23 Answers
    97%
    Delivers good value for the price
    77 Answers
    Happy with the feature set
    96%
    Happy with the feature set
    22 Answers
    92%
    Happy with the feature set
    116 Answers
    Lived up to sales and marketing promises
    100%
    Lived up to sales and marketing promises
    17 Answers
    97%
    Lived up to sales and marketing promises
    68 Answers
    Implementation went as expected
    95%
    Implementation went as expected
    20 Answers
    97%
    Implementation went as expected
    77 Answers
    Features
    Jupyter NotebookSigma
    Platform Connectivity
    Comparison of Platform Connectivity features of Jupyter Notebook and Sigma Computing
    Feature
    Jupyter Notebook
    9.0
    22 Ratings
    7% above category average
    Sigma Computing
    -
    Ratings
    Connect to Multiple Data Sources10.022 Ratings00 Ratings
    Extend Existing Data Sources10.021 Ratings00 Ratings
    Automatic Data Format Detection8.514 Ratings00 Ratings
    MDM Integration7.415 Ratings00 Ratings
    Data Exploration
    Comparison of Data Exploration features of Jupyter Notebook and Sigma Computing
    Feature
    Jupyter Notebook
    7.0
    22 Ratings
    19% below category average
    Sigma Computing
    -
    Ratings
    Visualization6.022 Ratings00 Ratings
    Interactive Data Analysis8.022 Ratings00 Ratings
    Data Preparation
    Comparison of Data Preparation features of Jupyter Notebook and Sigma Computing
    Feature
    Jupyter Notebook
    9.5
    22 Ratings
    15% above category average
    Sigma Computing
    -
    Ratings
    Interactive Data Cleaning and Enrichment10.021 Ratings00 Ratings
    Data Transformations10.022 Ratings00 Ratings
    Data Encryption8.514 Ratings00 Ratings
    Built-in Processors9.314 Ratings00 Ratings
    Platform Data Modeling
    Comparison of Platform Data Modeling features of Jupyter Notebook and Sigma Computing
    Feature
    Jupyter Notebook
    9.3
    22 Ratings
    9% above category average
    Sigma Computing
    -
    Ratings
    Multiple Model Development Languages and Tools10.021 Ratings00 Ratings
    Automated Machine Learning9.218 Ratings00 Ratings
    Single platform for multiple model development10.022 Ratings00 Ratings
    Self-Service Model Delivery8.020 Ratings00 Ratings
    Model Deployment
    Comparison of Model Deployment features of Jupyter Notebook and Sigma Computing
    Feature
    Jupyter Notebook
    10.0
    20 Ratings
    16% above category average
    Sigma Computing
    -
    Ratings
    Flexible Model Publishing Options10.020 Ratings00 Ratings
    Security, Governance, and Cost Controls10.019 Ratings00 Ratings
    BI Standard Reporting
    Comparison of BI Standard Reporting features of Jupyter Notebook and Sigma Computing
    Feature
    Jupyter Notebook
    -
    Ratings
    Sigma Computing
    7.5
    163 Ratings
    8% below category average
    Pixel Perfect reports00 Ratings5.4104 Ratings
    Customizable dashboards00 Ratings9.3161 Ratings
    Report Formatting Templates00 Ratings7.7133 Ratings
    Ad-hoc Reporting
    Comparison of Ad-hoc Reporting features of Jupyter Notebook and Sigma Computing
    Feature
    Jupyter Notebook
    -
    Ratings
    Sigma Computing
    7.5
    166 Ratings
    6% below category average
    Drill-down analysis00 Ratings8.0155 Ratings
    Formatting capabilities00 Ratings7.0163 Ratings
    Integration with R or other statistical packages00 Ratings7.35 Ratings
    Report sharing and collaboration00 Ratings7.7162 Ratings
    Report Output and Scheduling
    Comparison of Report Output and Scheduling features of Jupyter Notebook and Sigma Computing
    Feature
    Jupyter Notebook
    -
    Ratings
    Sigma Computing
    7.5
    156 Ratings
    9% below category average
    Publish to Web00 Ratings7.3103 Ratings
    Publish to PDF00 Ratings7.7130 Ratings
    Report Versioning00 Ratings7.0120 Ratings
    Report Delivery Scheduling00 Ratings7.6132 Ratings
    Delivery to Remote Servers00 Ratings7.968 Ratings
    Data Discovery and Visualization
    Comparison of Data Discovery and Visualization features of Jupyter Notebook and Sigma Computing
    Feature
    Jupyter Notebook
    -
    Ratings
    Sigma Computing
    6.8
    149 Ratings
    16% below category average
    Pre-built visualization formats (heatmaps, scatter plots etc.)00 Ratings8.6147 Ratings
    Location Analytics / Geographic Visualization00 Ratings5.626 Ratings
    Predictive Analytics00 Ratings6.218 Ratings
    Best Alternatives
    Jupyter NotebookSigma
    Small Businesses
    RapidMiner
    Score8.9 out of 10
    Cyfe
    Score4 out of 10
    Medium-sized Companies
    Anaconda
    Score8.8 out of 10
    Qlik Cloud Analytics (Qlik Sense)
    Score8.1 out of 10
    Enterprises
    IBM Watson Studio
    Score10 out of 10
    Sisense
    Score6.9 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    Jupyter NotebookSigma
    Likelihood to Recommend
    10.0
    (23 ratings)
    8.2
    (170 ratings)
    Likelihood to Renew
    -
    (0 ratings)
    10.0
    (6 ratings)
    Usability
    10.0
    (2 ratings)
    7.6
    (48 ratings)
    Availability
    -
    (0 ratings)
    8.2
    (2 ratings)
    Performance
    -
    (0 ratings)
    9.1
    (2 ratings)
    Support Rating
    9.0
    (1 ratings)
    10.0
    (47 ratings)
    Implementation Rating
    -
    (0 ratings)
    9.1
    (2 ratings)
    Configurability
    -
    (0 ratings)
    7.3
    (1 ratings)
    Ease of integration
    -
    (0 ratings)
    9.1
    (1 ratings)
    Product Scalability
    -
    (0 ratings)
    8.2
    (2 ratings)
    Vendor post-sale
    -
    (0 ratings)
    7.3
    (1 ratings)
    User Testimonials
    Jupyter NotebookSigma
    Likelihood to Recommend
    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.
    Incentivized
    Read full review
    Sigma Computing
    We were able to set up client-facing embedded reports with ease and security. The interface is not difficult to learn, although we may not be aware of or lack the necessary expertise to utilize more advanced features that would likely benefit us.
    Incentivized
    Read full review
    Pros
    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.
    Incentivized
    Read full review
    Sigma Computing
    • Allows end users to easily dive into the data without having direct access to the table in our database management software.
    • Can easily turnaround dashboards that are detailed and visually pleasing.
    • Sigma is intuitive and as new features are rolled out it is easy to adopt and incorporate them into new and existing dashboards.
    Incentivized
    Read full review
    Cons
    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.
    Incentivized
    Read full review
    Sigma Computing
    • Sigma Computing does not allow custom ordering of pivot fields in pivot tables easily
    • Sigma Computing lacks functionality for creating tables or sections that dynamically adjust to the browser window's height while maintaining a fixed height textbox at the bottom
    • Sigma Computing does not provide straightforward options for formatting totals in tables, such as renaming 'Total' to 'Average', 'Team Total', etc
    • Sigma Computing does not support searching by individual tab names within a workbook
    Incentivized
    Read full review
    Likelihood to Renew
    Open Source
    No answers on this topic
    Sigma Computing
    Sigma has helped us a lot and has become an integral part of our daily workflow. It would be difficult to switch to another platform and have to rebuild the numerous metrics and performance reports that we have already established
    Incentivized
    Read full review
    Usability
    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.
    Incentivized
    Read full review
    Sigma Computing
    It has a clean and modern interface. However, it is not completely intuitive. I think it would be better and easier to navigate with more Windows style drop down menus and/or tabls. There is a significant learning curve, but that may be due in part to the technical nature of this type of software tool.
    Incentivized
    Read full review
    Reliability and Availability
    Open Source
    No answers on this topic
    Sigma Computing
    Yes, as long as you don’t conduct user error sigma is always up and running and waiting for you to complete your dashboards
    Incentivized
    Read full review
    Performance
    Open Source
    No answers on this topic
    Sigma Computing
    It depends, it loads quickly for smaller dashboards but when loading larger amounts of data it takes more time to do so
    Incentivized
    Read full review
    Support Rating
    Open Source
    I haven't had a need to contact support. However, all required help is out there in public forums.
    Incentivized
    Read full review
    Sigma Computing
    They are very friendly and informative. They are quick in resolving our queries and help us understand very minute things as well. They are quick in creating feature tickets based on our custom requirements, and they would also create a bug ticket if there is any discrepancy and get that checked on time.
    Incentivized
    Read full review
    Implementation Rating
    Open Source
    No answers on this topic
    Sigma Computing
    Was not involved in implementation
    Incentivized
    Read full review
    Alternatives Considered
    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.
    Incentivized
    Read full review
    Sigma Computing
    With Looker, to be effective, a substantial amount of coding & modeling needs to happen in LookML. Being another language to learn, users have to context switch again from at a minimum either SQL or Python into LookML. The concept of being able to source control, code review, and deploy your models is a plus though.
    Tableau is the gold standard for data visualization, no question. Power users will be able to create dazzling content that Sigma won't necessarily be able to easily match. However, since development usually happens via an extract, helping other users troubleshoot is an arduous process. Trying to re-do or un-do all the transformations and calculations that cause a certain number is very difficult.
    With Sigma, all the queries happen directly against Snowflake and you can see the query logs. The data modeling happens right in a tabular, spreadsheet-like manner, so within only a few minutes, substantial transformations can happen, with visualizations just a few more clicks away.
    Read full review
    Scalability
    Open Source
    No answers on this topic
    Sigma Computing
    It is a cloud service offering that is able to expand based on your usage
    Incentivized
    Read full review
    Return on Investment
    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
    Incentivized
    Read full review
    Sigma Computing
    • Monitoring health of cloud platform has allowed the company to anticipate issues before they affect customers – Sigma prompted us building a canary monitoring process that provides customer container health.
    • Customer success has used an activity report to discover customers running runaway processes that they were unaware of, creating an alert to contact the customer and prevent an embarrassing situation.
    • Customer success uses the activity report to prompt conversations regarding increases or declines in behavior that led to increasing contract limits or addressing churn concerns.
    Incentivized
    Read full review
    ScreenShots