Software Alternatives, Accelerators & Startups

Apache Zeppelin VS Apache Airflow

Compare Apache Zeppelin VS Apache Airflow and see what are their differences

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Apache Zeppelin logo Apache Zeppelin

A web-based notebook that enables interactive data analytics.

Apache Airflow logo Apache Airflow

Airflow is a platform to programmaticaly author, schedule and monitor data pipelines.
  • Apache Zeppelin Landing page
    Landing page //
    2023-07-21
  • Apache Airflow Landing page
    Landing page //
    2023-06-17

Apache Zeppelin features and 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.

Possible disadvantages of Apache Zeppelin

  • Steeper Learning Curve
    For beginners, the learning curve for Apache Zeppelin can be quite steep, especially if they are not familiar with the command-line interface or the underlying technologies like Apache Spark or Hadoop.
  • Performance Issues
    Zeppelin can face performance issues when handling very large datasets or complex visualizations, potentially leading to slower response times or the need for significant hardware resources.
  • Limited Language Support
    While Zeppelin supports multiple languages through its interpreters, it doesn't support as many languages as some other data science tools, which could be a limitation for some users.
  • Security Concerns
    Since Apache Zeppelin allows code execution on the server, there are inherent security risks. Proper security measures must be in place to prevent unauthorized access and code execution, which can complicate setup and maintenance.
  • Dependency Management
    Managing dependencies and interpreter configurations in Zeppelin can be cumbersome, particularly in complex projects with multiple dependencies. This can lead to configuration drift and other maintenance challenges.

Apache Airflow features and specs

  • Scalability
    Apache Airflow can scale horizontally, allowing it to handle large volumes of tasks and workflows by distributing the workload across multiple worker nodes.
  • Extensibility
    It supports custom plugins and operators, making it highly customizable to fit various use cases. Users can define their own tasks, sensors, and hooks.
  • Visualization
    Airflow provides an intuitive web interface for monitoring and managing workflows. The interface allows users to visualize DAGs, track task statuses, and debug failures.
  • Flexibility
    Workflows are defined using Python code, which offers a high degree of flexibility and programmatic control over the tasks and their dependencies.
  • Integrations
    Airflow has built-in integrations with a wide range of tools and services such as AWS, Google Cloud, and Apache Hadoop, making it easier to connect to external systems.

Possible disadvantages of Apache Airflow

  • Complexity
    Setting up and configuring Apache Airflow can be complex, particularly for new users. It requires careful management of infrastructure components like databases and web servers.
  • Resource Intensive
    Airflow can be resource-heavy in terms of both memory and CPU usage, especially when dealing with a large number of tasks and DAGs.
  • Learning Curve
    The learning curve can be steep for users who are not familiar with Python or the underlying concepts of workflow management.
  • Limited Real-Time Processing
    Airflow is better suited for batch processing and scheduled tasks rather than real-time event-based processing.
  • Dependency Management
    Managing task dependencies in complex DAGs can become cumbersome and may lead to configuration errors if not properly handled.

Apache Zeppelin videos

Apache Zeppelin Meetup

Apache Airflow videos

Airflow Tutorial for Beginners - Full Course in 2 Hours 2022

Category Popularity

0-100% (relative to Apache Zeppelin and Apache Airflow)
Office & Productivity
100 100%
0% 0
Workflow Automation
0 0%
100% 100
IDE
100 100%
0% 0
Automation
0 0%
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Apache Zeppelin and Apache Airflow

Apache Zeppelin Reviews

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,...
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...

Apache Airflow Reviews

5 Airflow Alternatives for Data Orchestration
While Apache Airflow continues to be a popular tool for data orchestration, the alternatives presented here offer a range of features and benefits that may better suit certain projects or team preferences. Whether you prioritize simplicity, code-centric design, or the integration of machine learning workflows, there is likely an alternative that meets your needs. By...
Top 8 Apache Airflow Alternatives in 2024
Apache Airflow is a workflow streamlining solution aiming at accelerating routine procedures. This article provides a detailed description of Apache Airflow as one of the most popular automation solutions. It also presents and compares alternatives to Airflow, their characteristic features, and recommended application areas. Based on that, each business could decide which...
Source: blog.skyvia.com
10 Best Airflow Alternatives for 2024
In a nutshell, you gained a basic understanding of Apache Airflow and its powerful features. On the other hand, you understood some of the limitations and disadvantages of Apache Airflow. Hence, this article helped you explore the best Apache Airflow Alternatives available in the market. So, you can try hands-on on these Airflow Alternatives and select the best according to...
Source: hevodata.com
A List of The 16 Best ETL Tools And Why To Choose Them
Apache Airflow is an open-source platform to programmatically author, schedule, and monitor workflows. The platform features a web-based user interface and a command-line interface for managing and triggering workflows.
15 Best ETL Tools in 2022 (A Complete Updated List)
Apache Airflow programmatically creates, schedules and monitors workflows. It can also modify the scheduler to run the jobs as and when required.

Social recommendations and mentions

Based on our record, Apache Airflow should be more popular than Apache Zeppelin. It has been mentiond 75 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Apache Zeppelin mentions (9)

  • 📊 Visualise Presto Queries with Apache Zeppelin: A Hands-On Guide
    In the previous article, we explored the installation of Presto. Building on that foundation, it's time to take your data exploration one step further by integrating Presto with Apache Zeppelin, a powerful web-based notebook that allows interactive data analytics. - Source: dev.to / 6 days ago
  • 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 / over 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: about 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
View more

Apache Airflow mentions (75)

  • The DOJ Still Wants Google to Sell Off Chrome
    Is this really true? Something that can be supported by clear evidence? I’ve seen this trotted out many times, but it seems like there are interesting Apache projects: https://airflow.apache.org/ https://iceberg.apache.org/ https://kafka.apache.org/ https://superset.apache.org/. - Source: Hacker News / 2 months ago
  • 10 Must-Know Open Source Platform Engineering Tools for AI/ML Workflows
    Apache Airflow offers simplicity when it comes to scheduling, authoring, and monitoring ML workflows using Python. The tool's greatest advantage is its compatibility with any system or process you are running. This also eliminates manual intervention and increases team productivity, which aligns with the principles of Platform Engineering tools. - Source: dev.to / 3 months ago
  • Data Orchestration Tool Analysis: Airflow, Dagster, Flyte
    Data orchestration tools are key for managing data pipelines in modern workflows. When it comes to tools, Apache Airflow, Dagster, and Flyte are popular tools serving this need, but they serve different purposes and follow different philosophies. Choosing the right tool for your requirements is essential for scalability and efficiency. In this blog, I will compare Apache Airflow, Dagster, and Flyte, exploring... - Source: dev.to / 4 months ago
  • AIOps, DevOps, MLOps, LLMOps – What’s the Difference?
    Data pipelines: Apache Kafka and Airflow are often used for building data pipelines that can continuously feed data to models in production. - Source: dev.to / 4 months ago
  • Data Engineering with DLT and REST
    This article demonstrates how to work with near real-time and historical data using the dlt package. Whether you need to scale data access across the enterprise or provide historical data for post-event analysis, you can use the same framework to provide customer data. In a future article, I'll demonstrate how to use dlt with a workflow orchestrator such as Apache Airflow or Dagster.``. - Source: dev.to / 6 months ago
View more

What are some alternatives?

When comparing Apache Zeppelin and Apache Airflow, you can also consider the following products

Now Platform - Get native platform intelligence, so you can predict, prioritize, and proactively manage the work that matters most with the NOW Platform from ServiceNow.

Make.com - Tool for workflow automation (Former Integromat)

Amazon SageMaker - Amazon SageMaker provides every developer and data scientist with the ability to build, train, and deploy machine learning models quickly.

ifttt - IFTTT puts the internet to work for you. Create simple connections between the products you use every day.

Adobe Flash Builder - If you are facing issues while downloading your Creative Cloud apps, use the download links in the table below.

Microsoft Power Automate - Microsoft Power Automate is an automation platform that integrates DPA, RPA, and process mining. It lets you automate your organization at scale using low-code and AI.