For evolving schema and high compatibility, which data format should be chosen for downstream analytics?

CSV is a simple text format with no built-in schema, making schema evolution difficult to manage and prone to errors.

JSON is self-describing but does not enforce a strict schema and handling schema evolution robustly across different versions can be complex without additional tooling.

Parquet is a columnar format optimized for analytical queries and compression, but its schema evolution capabilities, while present, are generally less flexible or robust than Avro for complex schema changes.

Avro is a row-oriented data format that includes the schema with the data, allowing for excellent schema evolution. This means applications can read data written with an older or newer schema without breaking, ensuring high compatibility and flexibility for evolving analytical requirements.