Apache Avro is a row-oriented remote procedure call and data serialization framework developed within Apache's Hadoop project. It uses JSON for defining data types and protocols, and serializes data in a compact binary format.
Avro is designed to support complex nested data structures and enables efficient querying and manipulation of specific columns without reading the entire dataset.
Apache Parquet is a columnar storage format optimized for use with big data processing frameworks. It offers efficient data compression and encoding schemes, which leads to significant storage savings and improved read performance.
Parquet is designed to support complex nested data structures and enables efficient querying and manipulation of specific columns without reading the entire dataset.
Parquet supports various compression algorithms such as Snappy, Gzip, and LZO. These compression techniques help in reducing the storage space and improving the performance of data processing tasks.