Apache Zeppelin Reviews and details

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2023-07-21

Features & Specs

Interactive Data Exploration

Apache Zeppelin supports interactive data exploration and visualization. Users can write code in multiple languages (e.g., SQL, Python, R) and immediately see the results, enabling dynamic data analysis.
Multi-language Support

Zeppelin supports multiple languages and backend systems through its interpreters, including Apache Spark, Python, JDBC, and more. This makes it versatile for data scientists and analysts who work with different technologies.
Collaborative Environment

Zeppelin provides a collaborative environment where multiple users can share notebooks and insights. This fosters team collaboration and enhances productivity among data teams.
Integration with Big Data Tools

Zeppelin integrates well with big data tools like Apache Spark, Hadoop, and various data storage solutions, making it an excellent choice for large-scale data processing and analysis tasks.
Custom Visualizations

Users can create rich, custom visualizations with Zeppelin's built-in visualization tools or by leveraging libraries like D3.js. This helps in presenting data insights in a more understandable and visually appealing manner.

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Videos

Apache Zeppelin Meetup

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Social recommendations and mentions

We have tracked the following product recommendations or mentions on various public social media platforms and blogs. They can help you see what people think about Apache Zeppelin and what they use it for.

Serverless Data Processing on AWS : AWS Project
To do so, we will use Kinesis Data Analytics to run an Apache Flink application. To enhance our development experience, we will use Studio notebooks for Kinesis Data Analytics that are powered by Apache Zeppelin. - Source: dev.to / 6 months ago
Serverless Apache Zeppelin on AWS
Now we can proceed with the definition of Apache Zeppelin. It is a web-based notebook that enables data-driven, interactive data analytics and collaborative documents with Python, Scala, SQL, Spark, and more. You can execute code and even schedule a job (via cron) to run at regular intervals. - Source: dev.to / about 1 year ago
Visualization using Pyspark Dataframe
Have you tried Apache Zepellin I remember that you can pretty print spark dataframes directly on it with z.show(df). Source: almost 3 years ago
Fast CSV Processing with SIMD
I used to use Zeppelin, some kind of Jupyter Notebook for Spark (that supports Parquet). But it may be better alternatives. https://zeppelin.apache.org/. - Source: Hacker News / over 3 years ago
What libraries do you use for machine learning and data visualizing in scala?
Another more widely used notebooks for scala and spark: Https://zeppelin.apache.org/. Source: over 3 years ago
Dataflow, a self-hosted Observable Notebook Editor
Apache Zeppelin is one open source option - https://zeppelin.apache.org. - Source: Hacker News / almost 4 years ago
Using InterSystems Caché and Apache Zeppelin
For all who think: What the heck is Apache Zeppelin? Here are some details what the project site says:. - Source: dev.to / about 4 years ago
Is there a way to collaborate in real-time for Jupyter Notebooks?
Check out Zeppelin. It's similar to Jupyter and allows real-time editing by multiple users. https://zeppelin.apache.org/. Source: about 4 years ago

External sources with reviews and comparisons of Apache Zeppelin

12 Best Jupyter Notebook Alternatives [2023] – Features, pros & cons, pricing

Apache Zeppelin is an open-source platform for data science and analytics that is similar to Jupyter Notebooks. It allows users to write and execute code in a variety of programming languages, as well as include text, equations, and visualizations in a single document. Apache Zeppelin also has a built-in code editor and supports a wide range of libraries and frameworks, including TensorFlow and PyTorch.

Source: noteable.io

The Best ML Notebooks And Infrastructure Tools For Data Scientists

Apache Zeppelin is another web-based open-source notebook popular among data scientists. The platform supports three languages – SQL, Python, and R. Zeppelin also backs interpreters such as Apache Spark, JDBC, Markdown, Shell, and Hadoop. The built-in basic charts and pivot table structures help to create input forms in the notebook. Zeppelin can be shared on Github and offers resizable notebook cells as a unique...

Source: analyticsindiamag.com

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