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  5. Apache Zeppelin vs Power BI

Apache Zeppelin vs Power BI

OverviewDecisionsComparisonAlternatives

Overview

Apache Zeppelin
Apache Zeppelin
Stacks190
Followers306
Votes32
GitHub Stars6.6K
Forks2.8K
Power BI
Power BI
Stacks991
Followers946
Votes29

Apache Zeppelin vs Power BI: What are the differences?

Key Differences Between Apache Zeppelin and Power BI

Apache Zeppelin and Power BI are two popular data analysis and visualization tools used by data professionals. While both tools have similar objectives, they differ in a few key areas. Here are the key differences between Apache Zeppelin and Power BI:

  1. Framework and Technology Stack: Apache Zeppelin is an open-source web-based notebook that supports multiple programming languages such as Python, Scala, SQL, and more. It provides a flexible and extensible platform for data analysis and visualization. On the other hand, Power BI is a business intelligence tool developed by Microsoft, primarily focused on data visualization and reporting. It has a more restricted framework and supports limited programming languages.

  2. Data Source Connectivity: Apache Zeppelin offers a wide range of connectors and integrations with various data sources, including Hadoop, Spark, SQL databases, and NoSQL databases. It provides seamless integration with these data sources, allowing users to access and analyze data from multiple platforms. Power BI, although it supports various data sources, has a stronger integration with Microsoft products like Azure, Excel, and SQL Server.

  3. Data Transformations and Analysis: Apache Zeppelin provides a powerful and flexible environment for data transformations and analysis. It allows users to write custom code using different programming languages and libraries, enabling complex data manipulations. Power BI, on the other hand, offers a more user-friendly interface with drag-and-drop functionality and pre-built visualizations. It focuses on providing a simpler and intuitive experience for non-technical users.

  4. Collaboration and Sharing: Apache Zeppelin emphasizes collaboration and sharing among users. It enables multiple users to work on the same notebook simultaneously, making it easier for teams to collaborate on data analysis projects. It also allows users to share notebooks and visualizations with others through URLs. Power BI, although it supports collaboration and sharing to some extent, is more geared towards individual use and lacks the same level of real-time collaboration features as Zeppelin.

  5. Deployment Options: Apache Zeppelin can be deployed both on-premises and on cloud platforms like Amazon Web Services (AWS) and Google Cloud Platform (GCP). It provides greater flexibility in terms of deployment and can be customized according to specific requirements. Power BI, on the other hand, is primarily a cloud-based tool, although it does offer on-premises options with Power BI Report Server.

  6. Licensing and Cost: Apache Zeppelin is an open-source tool and is available for free. It can be used without any licensing fees, making it a cost-effective option for organizations on a budget. Power BI, on the other hand, has both free and paid versions. The free version offers limited functionality and has certain limitations, while the paid version, Power BI Pro, comes with additional features and capabilities but requires a subscription.

In summary, the key differences between Apache Zeppelin and Power BI lie in their framework and technology stack, data source connectivity, data transformations and analysis capabilities, collaboration and sharing features, deployment options, and licensing and cost models. While Zeppelin focuses on flexibility, customization, and collaboration, Power BI prioritizes ease of use, Microsoft product integration, and cloud-based deployment.

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Advice on Apache Zeppelin, Power BI

Vojtech
Vojtech

Head of Data at Mews

Nov 24, 2019

Decided

Power BI is really easy to start with. If you have just several Excel sheets or CSV files, or you build your first automated pipeline, it is actually quite intuitive to build your first reports.

And as we have kept growing, all the additional features and tools were just there within the Azure platform and/or Office 365.

Since we started building Mews, we have already passed several milestones in becoming start up, later also a scale up company and now getting ready to grow even further, and during all these phases Power BI was just the right tool for us.

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Comments

Detailed Comparison

Apache Zeppelin
Apache Zeppelin
Power BI
Power BI

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 aims to provide interactive visualizations and business intelligence capabilities with an interface simple enough for end users to create their own reports and dashboards.

-
Get self-service analytics at enterprise scale; Use smart tools for strong results; Help protect your analytics data
Statistics
GitHub Stars
6.6K
GitHub Stars
-
GitHub Forks
2.8K
GitHub Forks
-
Stacks
190
Stacks
991
Followers
306
Followers
946
Votes
32
Votes
29
Pros & Cons
Pros
  • 7
    In-line code execution using paragraphs
  • 5
    Cluster integration
  • 4
    Zeppelin context to exchange data between languages
  • 4
    In-line graphing
  • 4
    Multi-User Capability
Pros
  • 18
    Cross-filtering
  • 4
    Database visualisation
  • 2
    Intuitive and complete internal ETL
  • 2
    Access from anywhere
  • 2
    Powerful Calculation Engine
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
Microsoft Excel
Microsoft Excel

What are some alternatives to Apache Zeppelin, Power BI?

Metabase

Metabase

It is an easy way to generate charts and dashboards, ask simple ad hoc queries without using SQL, and see detailed information about rows in your Database. You can set it up in under 5 minutes, and then give yourself and others a place to ask simple questions and understand the data your application is generating.

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.

Superset

Superset

Superset's main goal is to make it easy to slice, dice and visualize data. It empowers users to perform analytics at the speed of thought.

Cube

Cube

Cube: the universal semantic layer that makes it easy to connect BI silos, embed analytics, and power your data apps and AI with context.

Mode

Mode

Created by analysts, for analysts, Mode is a SQL-based analytics tool that connects directly to your database. Mode is designed to alleviate the bottlenecks in today's analytical workflow and drive collaboration around data projects.

Google Datastudio

Google Datastudio

It lets you create reports and data visualizations. Data Sources are reusable components that connect a report to your data, such as Google Analytics, Google Sheets, Google AdWords and so forth. You can unlock the power of your data with interactive dashboards and engaging reports that inspire smarter business decisions.

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.

AskNed

AskNed

AskNed is an analytics platform where enterprise users can get answers from their data by simply typing questions in plain English.

Shiny

Shiny

It is an open source R package that provides an elegant and powerful web framework for building web applications using R. It helps you turn your analyses into interactive web applications without requiring HTML, CSS, or JavaScript knowledge.

Redash

Redash

Redash helps you make sense of your data. Connect and query your data sources, build dashboards to visualize data and share them with your company.

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