Amundsen vs Apache Parquet: What are the differences?

Introduction

In the world of data management, Amundsen and Apache Parquet serve different purposes and functions. Here are the key differences between these two technologies.

1. Data Storage Format: Apache Parquet is a columnar storage format optimized for analytics. It stores data in columns rather than rows, making it efficient for query performance and compression. On the other hand, Amundsen is a metadata catalog service that provides a centralized repository for metadata and data discovery.

2. Use Case: Apache Parquet is used primarily for structured data storage and analysis, making it ideal for big data processing tools like Hadoop and Spark. Amundsen, on the other hand, is used for data discovery and collaboration, enabling users to find, understand, and use data assets effectively.

3. Integration: Apache Parquet can be integrated with a wide range of data processing frameworks and tools like Hive, Impala, and Drill. It is widely supported in the big data ecosystem. Amundsen, on the other hand, integrates with existing data sources, data warehouses, and business intelligence tools to provide a cohesive data discovery experience.

4. Functionality: Apache Parquet focuses on optimizing storage and query performance for analytical workloads. It supports efficient data compression and encoding techniques. Amundsen, on the other hand, focuses on metadata management, data lineage, and data governance, providing users with a comprehensive view of their data assets.

5. User Audience: Apache Parquet is mainly targeted towards data engineers, data scientists, and analysts who work with large datasets and require efficient data storage and processing. Amundsen, on the other hand, targets data stewards, data analysts, and business users who need to explore and understand data assets within their organization.

6. Scalability: Apache Parquet is highly scalable and designed for parallel processing, making it suitable for large-scale data processing tasks. Amundsen, on the other hand, can scale to accommodate large metadata catalogs and data discovery needs within an organization.

In summary, Apache Parquet is a columnar storage format optimized for analytics, while Amundsen is a metadata catalog service focused on data discovery and collaboration.