Apache Zeppelin vs Databricks

Overview

Apache Zeppelin

Stacks190

Followers306

Votes32

GitHub Stars6.6K

Forks2.8K

Databricks

Stacks525

Followers768

Votes8

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.

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.
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.
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.
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.
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.
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.

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CLI (Node.js)

Manual

Detailed Comparison

Apache Zeppelin	Databricks
A web-based notebook that enables interactive data analytics. You can make beautiful data-driven, interactive and collaborative documents with SQL, Scala and more.	Databricks Unified Analytics Platform, from the original creators of Apache Spark™, unifies data science and engineering across the Machine Learning lifecycle from data preparation to experimentation and deployment of ML applications.
-	Built on Apache Spark and optimized for performance; Reliable and Performant Data Lakes; Interactive Data Science and Collaboration; Data Pipelines and Workflow Automation; End-to-End Data Security and Compliance; Compatible with Common Tools in the Ecosystem; Unparalled Support by the Leading Committers of Apache Spark
Statistics
GitHub Stars 6.6K	GitHub Stars -
GitHub Forks 2.8K	GitHub Forks -
Stacks 190	Stacks 525
Followers 306	Followers 768
Votes 32	Votes 8
Pros & Cons
Pros 7 In-line code execution using paragraphs 5 Cluster integration 4 Multi-User Capability 4 Zeppelin context to exchange data between languages 4 In-line graphing	Pros 1 Scalability 1 Multicloud 1 Data stays in your cloud account 1 Security 1 Usage Based Billing
Integrations
Cassandra Apache Spark R Language PostgreSQL Elasticsearch HBase Hadoop Apache Flink Python	MLflow Delta Lake Kafka Apache Spark TensorFlow Hadoop PyTorch Keras

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Related Comparisons

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.

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.
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.
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.
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.
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.
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.

Apache Zeppelin vs Databricks

Overview