Apache Parquet

Definition: Apache Parquet is an open-source, column-oriented data storage format used within the Apache Hadoop ecosystem. It is designed for efficient data compression and encoding, facilitating high-performance analytics on complex data structures.

Evolution: Developed through a collaboration between Twitter and Cloudera, Parquet was created to enhance the capabilities of the columnar storage format, improving upon earlier versions like Trevni by Doug Cutting, Hadoop’s creator.

Key Features:

• Efficient Data Storage: Utilizes columnar storage approach for optimal compression and efficient disk storage.
• Enhanced Performance: Optimizes analytical query performance by allowing selective data access and reducing I/O operations.
• Compatibility: Works seamlessly with a variety of data processing frameworks in the Hadoop ecosystem, including Apache Hive, Apache Spark, and more.

Benefits:

• Scalability: Suitable for handling large-scale data processing and analytics.
• Flexibility: Supports complex data types and structures, enabling diverse analytical applications.
• Community Support: As a top-level Apache project, it benefits from robust community support and continuous development.

Apache Parquet represents a significant advancement in data storage technology, offering an efficient and scalable solution for big data analytics challenges.