StackShareStackShare
Follow on
StackShare

Discover and share technology stacks from companies around the world.

Follow on

© 2025 StackShare. All rights reserved.

Product

  • Stacks
  • Tools
  • Feed

Company

  • About
  • Contact

Legal

  • Privacy Policy
  • Terms of Service
  1. Stackups
  2. Application & Data
  3. Databases
  4. Big Data Tools
  5. Apache Zeppelin vs Hue

Apache Zeppelin vs Hue

OverviewComparisonAlternatives

Overview

Hue
Hue
Stacks55
Followers98
Votes0
Apache Zeppelin
Apache Zeppelin
Stacks190
Followers306
Votes32
GitHub Stars6.6K
Forks2.8K

Apache Zeppelin vs Hue: What are the differences?

Introduction

Apache Zeppelin and Hue are both web-based UI tools that provide a graphical interface for interacting with big data platforms. While they have some similarities, there are key differences between the two.

  1. Architecture:

Apache Zeppelin is built using a notebook architecture, where users can create and execute code in individual paragraphs. It supports multiple interpreters and languages, allowing users to work with different data processing engines. Hue, on the other hand, follows a traditional web application architecture, providing a centralized interface for various applications like Hive, Pig, and Impala.

  1. Support for Data Processing Engines:

Zeppelin is more focused on data analysis and exploration, providing support for engines like Spark, Hive, and SQL through interpreters. It allows users to create visualizations and perform data manipulation tasks within the notebook environment. Hue, on the other hand, acts as a gateway to different data processing engines, providing a unified interface for managing and running jobs across multiple platforms.

  1. Collaboration and Sharing:

Zeppelin provides collaboration features, allowing multiple users to work on the same notebook simultaneously. It also supports sharing and exporting notebooks, making it easy to share analyses with others. Hue, while lacking real-time collaboration, provides a comprehensive sharing and scheduling framework that allows users to share queries, dashboards, and workflows with other team members.

  1. User Interface Design:

Zeppelin focuses on a notebook-style interface, where users can organize their code and visualizations in a structured manner. It provides a rich set of visualizations and interactive controls that can be embedded directly within the notebook. Hue, on the other hand, provides a more traditional web-based interface, with a menu-driven navigation that guides users through the various data processing applications.

  1. Extensibility and Customization:

Zeppelin allows users to extend its functionality by creating custom interpreters and visualizations. This makes it highly customizable and adaptable to specific use cases. Hue, while not as extensible as Zeppelin, provides integration with multiple data processing engines, allowing users to leverage their existing workflows and tools.

  1. Security and Access Control:

Zeppelin provides basic access control features, allowing users to authenticate and authorize access to notebooks. However, it lacks the comprehensive security features provided by Hue, which includes fine-grained access controls, SSL encryption, and integration with external authentication systems like LDAP and Kerberos.

In summary, Apache Zeppelin and Hue are web-based UI tools with different architectures, focuses, and features. Zeppelin is more geared towards data analysis and exploration, with its notebook-style interface and support for multiple data processing engines. Hue, on the other hand, acts as a gateway to different platforms, providing a centralized interface for managing and running jobs across various applications.

Share your Stack

Help developers discover the tools you use. Get visibility for your team's tech choices and contribute to the community's knowledge.

View Docs
CLI (Node.js)
or
Manual

Detailed Comparison

Hue
Hue
Apache Zeppelin
Apache Zeppelin

It is open source and lets regular users import their big data, query it, search it, visualize it and build dashboards on top of it, all from their browser.

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

Statistics
GitHub Stars
-
GitHub Stars
6.6K
GitHub Forks
-
GitHub Forks
2.8K
Stacks
55
Stacks
190
Followers
98
Followers
306
Votes
0
Votes
32
Pros & Cons
No community feedback yet
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
Integrations
No integrations available
Cassandra
Cassandra
Apache Spark
Apache Spark
R Language
R Language
PostgreSQL
PostgreSQL
Elasticsearch
Elasticsearch
HBase
HBase
Hadoop
Hadoop
Apache Flink
Apache Flink
Python
Python

What are some alternatives to Hue, Apache Zeppelin?

Apache Spark

Apache Spark

Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.

Presto

Presto

Distributed SQL Query Engine for Big Data

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.

Amazon Athena

Amazon Athena

Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run.

Apache Flink

Apache Flink

Apache Flink is an open source system for fast and versatile data analytics in clusters. Flink supports batch and streaming analytics, in one system. Analytical programs can be written in concise and elegant APIs in Java and Scala.

lakeFS

lakeFS

It is an open-source data version control system for data lakes. It provides a “Git for data” platform enabling you to implement best practices from software engineering on your data lake, including branching and merging, CI/CD, and production-like dev/test environments.

Druid

Druid

Druid is a distributed, column-oriented, real-time analytics data store that is commonly used to power exploratory dashboards in multi-tenant environments. Druid excels as a data warehousing solution for fast aggregate queries on petabyte sized data sets. Druid supports a variety of flexible filters, exact calculations, approximate algorithms, and other useful calculations.

Apache Kylin

Apache Kylin

Apache Kylin™ is an open source Distributed Analytics Engine designed to provide SQL interface and multi-dimensional analysis (OLAP) on Hadoop/Spark supporting extremely large datasets, originally contributed from eBay Inc.

Splunk

Splunk

It provides the leading platform for Operational Intelligence. Customers use it to search, monitor, analyze and visualize machine data.

Apache Impala

Apache Impala

Impala is a modern, open source, MPP SQL query engine for Apache Hadoop. Impala is shipped by Cloudera, MapR, and Amazon. With Impala, you can query data, whether stored in HDFS or Apache HBase – including SELECT, JOIN, and aggregate functions – in real time.

Related Comparisons

Bootstrap
Materialize

Bootstrap vs Materialize

Laravel
Django

Django vs Laravel vs Node.js

Bootstrap
Foundation

Bootstrap vs Foundation vs Material UI

Node.js
Spring Boot

Node.js vs Spring-Boot

Liquibase
Flyway

Flyway vs Liquibase