Apache Zeppelin vs Databricks: What are the differences?

Introduction

Apache Zeppelin and Databricks are both popular tools used in the field of big data analytics. While they serve a similar purpose, there are some key differences between the two that set them apart.

1. Integration with different frameworks: Apache Zeppelin provides a highly flexible and extensible environment for data analysis, with support for a wide range of programming languages such as Scala, Python, and R. Databricks, on the other hand, is tightly integrated with the Apache Spark platform, and offers a unified workspace for collaborative data engineering and machine learning.

2. Scalability and performance: Databricks is known for its scalability and performance optimization features. It allows users to effortlessly scale their analytics workloads by leveraging the power of the cloud, providing faster processing and execution times. Apache Zeppelin, while still capable of handling large datasets, may not offer the same level of scalability and performance as Databricks.

3. Support for structured streaming: Databricks is designed to seamlessly handle structured streaming, allowing users to process and analyze real-time data in a streaming fashion. Apache Zeppelin, while capable of working with streaming data, may require additional configurations and customizations to achieve the same level of real-time data processing capabilities.

4. Community and ecosystem: Apache Zeppelin has a vibrant open-source community that constantly contributes to its development, offering a wide range of plugins and integrations with various data sources and tools. Databricks, being a commercial platform, has a large user base and offers extensive support and resources, including tutorials, documentation, and enterprise-grade features.

5. User interface and collaboration features: Databricks provides a user-friendly web-based interface that enables collaborative data exploration and analysis, with features such as notebooks, version control, and interactive dashboards. Apache Zeppelin also offers similar features, but the user interface may vary in terms of functionality and ease of use.

6. Pricing and cost flexibility: Databricks is a commercial platform that follows a subscription-based pricing model. It offers different pricing plans based on the number of users and the desired level of features and capabilities. Apache Zeppelin, being an open-source tool, is free to use and can be deployed on any infrastructure without incurring additional costs.

In summary, Apache Zeppelin and Databricks differ in their integration with frameworks, scalability and performance, support for structured streaming, community and ecosystem, user interface and collaboration features, and pricing and cost flexibility.