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  4. Data Science Notebooks
  5. Apache Zeppelin vs Polynote

Apache Zeppelin vs Polynote

OverviewComparisonAlternatives

Overview

Apache Zeppelin
Apache Zeppelin
Stacks190
Followers306
Votes32
GitHub Stars6.6K
Forks2.8K
Polynote
Polynote
Stacks4
Followers9
Votes0
GitHub Stars4.6K
Forks393

Apache Zeppelin vs Polynote: What are the differences?

Introduction: Apache Zeppelin and Polynote are both popular tools used for interactive data analysis, but they have some key differences that set them apart.

  1. Integration with Different Data Sources: Apache Zeppelin supports integration with a wide range of data sources, including Apache Spark, Hive, and Cassandra. On the other hand, Polynote has built-in support for Scala and Python kernels but lacks out-of-the-box integration with as many data sources as Zeppelin.

  2. Notebook Customization and Layout: Apache Zeppelin provides a more customizable experience in terms of notebook layout and design compared to Polynote. Users can easily customize the appearance of their notebooks in Zeppelin, whereas Polynote offers a more standardized notebook layout.

  3. Language Support: While both Apache Zeppelin and Polynote support multiple programming languages, Zeppelin offers a broader range of language support including Scala, Python, R, and SQL. Polynote, on the other hand, focuses on providing optimal support for Scala and Python, with limited support for other languages.

  4. Git Integration: Apache Zeppelin has built-in integration with Git, which allows for version control and collaboration on notebooks. Polynote currently lacks native Git integration, making it more challenging to manage notebook versions and collaborate on projects.

  5. Security Features: Apache Zeppelin provides robust security features, including authentication, authorization, and encryption of data. Polynote also offers security features but may not be as comprehensive or customizable as Zeppelin in this aspect.

  6. Community Support and Updates: Apache Zeppelin has a larger user community and a more active development team, leading to more frequent updates, bug fixes, and new features compared to Polynote. Polynote, being a newer tool, may have a smaller community and slower update cycle.

In Summary, Apache Zeppelin and Polynote differ in terms of data source integration, notebook customization, language support, Git integration, security features, and community support and updates.

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Detailed Comparison

Apache Zeppelin
Apache Zeppelin
Polynote
Polynote

A web-based notebook that enables interactive data analytics. You can make beautiful data-driven, interactive and collaborative documents with SQL, Scala and more.

It is a different kind of notebook. It supports mixing multiple languages in one notebook, and sharing data between them seamlessly. It encourages reproducible notebooks with its immutable data model.

-
Code editing; Text editing; Multi-language support; Runtime insight
Statistics
GitHub Stars
6.6K
GitHub Stars
4.6K
GitHub Forks
2.8K
GitHub Forks
393
Stacks
190
Stacks
4
Followers
306
Followers
9
Votes
32
Votes
0
Pros & Cons
Pros
  • 7
    In-line code execution using paragraphs
  • 5
    Cluster integration
  • 4
    In-line graphing
  • 4
    Multi-User Capability
  • 4
    Zeppelin context to exchange data between languages
No community feedback yet
Integrations
Cassandra
Cassandra
Apache Spark
Apache Spark
R Language
R Language
PostgreSQL
PostgreSQL
Elasticsearch
Elasticsearch
HBase
HBase
Hadoop
Hadoop
Apache Flink
Apache Flink
Python
Python
Python
Python
Scala
Scala

What are some alternatives to Apache Zeppelin, Polynote?

Jupyter

Jupyter

The Jupyter Notebook is a web-based interactive computing platform. The notebook combines live code, equations, narrative text, visualizations, interactive dashboards and other media.

Deepnote

Deepnote

Deepnote is building the best data science notebook for teams. In the notebook, users can connect their data, explore and analyze it with real-time collaboration and versioning, and easily share and present the polished assets to end users.

Google Colaboratory

Google Colaboratory

It is a hosted Jupyter Notebook service that requires no setup to use and provides free access to computing resources, including GPUs and TPUs. Colab is especially well suited to machine learning, data science, and education.

SageMath

SageMath

It is a free open-source mathematics software system licensed under the GPL. It builds on top of many existing open-source packages: NumPy, SciPy, matplotlib, Sympy, Maxima, GAP, FLINT, R and many more.

Franchise

Franchise

Chart with a single click. Compare queries side by side. Download your work and share it with anyone. If your data is in a CSV, JSON, or XLSX file, loading it is as simple as dropping the file into Franchise.

Vayu

Vayu

It is an end-to-end tool for data science, without writing any code. Import, prepare, analyze, visualize and share in just a few clicks. Build interactive reports, automate workflows and share templates.

Starboard

Starboard

It is fully in-browser literate notebooks like Jupyter Notebook. It's probably the quickest way to visualize some data with interactivity, do some prototyping, or build a rudimentary dashboard.

Marimo

Marimo

It is a reactive notebook for Python. It allows you to rapidly experiment with data and models, code with confidence in your notebook’s correctness, and productionize notebooks as pipelines or interactive web apps.

mljar Mercury

mljar Mercury

It is the easiest way to turn your Python Notebooks into interactive web applications and publish to the cloud. It is dual-licensed. The main features are available in the open-source version. It is perfect for quick demos, educational purposes, sharing notebooks with friends.

Mineo

Mineo

It is the platform to explore your data, develop and deploy your Python supercharged Notebooks and track the quality of your data using Machine learning.

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