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Head-to-head · Notebook Software

Kaggle Notebooks vs Apache Zeppelin

  • Updated Oct 2026
  • Both researched from official sources
  • 4 checks side by side
Higher score Kaggle Notebooks #4 in Notebook Software 9.0/10 Free plan Free plan✓ 3 of 3 features Visit Kaggle
Apache Zeppelin #12 in Notebook Software 8.1/10 Open source ✓ 3 of 3 features Try Apache Zeppelin

Kaggle Notebooks leads on 0 checks, Apache Zeppelin on 0, and 4 are even. Who comes out ahead on the 4 yes/no, price and count checks where we have data for both products. The editor score weighs everything else too.

Our verdict

  • Highest scoreKaggle Notebooks · 9.0/10
  • Free planonly Kaggle Notebooks

Kaggle Notebooks scores higher on our rubric for notebook software: 9.0 against 8.1 out of 10; our editors rank them #4 and #12.

On execution model, Apache Zeppelin gives you Hybrid where Kaggle Notebooks offers Hosted.

Kaggle Notebooks is the better fit for free hosted notebooks with accelerators. Apache Zeppelin is the better fit for big-data and Spark notebook workflows.

  • Kaggle Notebooks fits best

    Free hosted notebooks with accelerators

  • Apache Zeppelin fits best

    Big-data and Spark notebook workflows

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Side by side

Feature Kaggle Notebooks 9.0/10 Visit ↗ Apache Zeppelin 8.1/10 Visit ↗
At a glance
Editor score 9.0 8.1
Ranking #4 in Notebook Software #12 in Notebook Software
Best for Free hosted notebooks with accelerators Big-data and Spark notebook workflows
Pricing model Free Free
Starting price Free plan Open source
Free plan ✓ (best) Not checked yet
Free trial — —
Deployment Cloud Self-hosted
Platforms Web Web, macOS, Linux
Support Docs, Community Community, Docs
Integrations 5 integrations 14 integrations
Built for Solo, Small business, Mid-market Small business, Mid-market, Enterprise
Features Kaggle Notebooks 3/3 · Apache Zeppelin 3/3
Real-time collaboration ✓ ✓
Version history ✓ ✓
GPU compute ✓ ✓
Specs
Execution model Hosted Hybrid
Supported languages Python, R Scala, Python, SQL, R, Java, Groovy, Shell, Markdown, SPARQL
Notebook formats .ipynb JSON, .zpln
Our review
Pros
  • Free hosted Jupyter execution with GPU and TPU accelerators
  • Docker-based environments with version snapshots and saved outputs
  • Collaboration, scheduled runs, and dataset or model inputs
  • Built-in Apache Spark integration with pluggable interpreters
  • Real-time collaboration, sharing, publishing, and Git versioning
  • Charts, tables, REST APIs, and Kubernetes GPU support
Cons
  • Notebook language support is limited to Python and R
  • The browser-based product is available on the web platform
  • Additional compute or customization points to Google Cloud AI Notebooks
  • Self-hosted deployment requires teams to manage infrastructure
  • Its data-platform focus is narrower than general Jupyter tools
  • GPU support depends on Kubernetes interpreter pods
Our verdict

Kaggle Notebooks is a browser-based notebook environment for data science and machine learning. It provides hosted Jupyter execution for Python and R, with .ipynb notebook support and optional GPU or TPU accelerators. Its inputs can…

Read the review →

Apache Zeppelin is a self-hosted, web-based notebook for interactive data analytics, visualization, and collaboration. It is aimed at data-platform teams and analysts who need notebooks that can connect to multiple languages, processing…

Read the review →
  1. Kaggle NotebooksNotebook Software 9.0Free plan
  2. Apache ZeppelinNotebook Software 8.1Open source

Strengths and trade-offs

  • Kaggle Notebooks — where it wins

    • Free hosted Jupyter execution with GPU and TPU accelerators
    • Docker-based environments with version snapshots and saved outputs
    • Collaboration, scheduled runs, and dataset or model inputs

    Where it doesn't

    • Notebook language support is limited to Python and R
    • The browser-based product is available on the web platform
    • Additional compute or customization points to Google Cloud AI Notebooks

  • Apache Zeppelin — where it wins

    • Built-in Apache Spark integration with pluggable interpreters
    • Real-time collaboration, sharing, publishing, and Git versioning
    • Charts, tables, REST APIs, and Kubernetes GPU support

    Where it doesn't

    • Self-hosted deployment requires teams to manage infrastructure
    • Its data-platform focus is narrower than general Jupyter tools
    • GPU support depends on Kubernetes interpreter pods

More comparisons

All notebook software comparisons → · Full ranking →

Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026

Last updated · How we research and update