Big data file formats are used to store and process large volumes of data efficiently. Some of the popular data formats include:

  1. Apache Avro: Avro is a row-based binary serialization format used for efficient data serialization and exchange between systems.
  2. Apache Parquet:Parquet is a columnar storage format optimized for analytics workloads, providing efficient storage and retrieval of columnar data.
  3. Apache ORC (Optimized Row Columnar): ORC is a columnar storage format designed for high performance and efficient query processing in Hadoop-based systems.
  4. JSON (JavaScript Object Notation): JSON is a lightweight, human-readable data interchange format used for transmitting and storing structured data.

Apart from that XML is also an option, however its verbose syntax and lack of efficient storage for big data volume makes it a less viable option.

Overall, the choice of file format depends on the exact use case for data ingestion, archival, and migration, along with factors such as such as the nature of the data, performance requirements, compatibility with existing systems, and long-term storage considerations. Organizations may choose to use different file formats for different stages of the data lifecycle to optimize storage, processing, and analysis efficiency.