Schema compatibility rules in Kafka - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is schema compatibility in Kafka?

Schema compatibility ensures that new versions of a schema can work with data written using older versions without errors.

beginner

Name the four main types of schema compatibility rules in Kafka.

Backward, Forward, Full, and None compatibility.

beginner

What does Backward compatibility mean?

New schema can read data written with the previous schema version, so consumers using the new schema can read old data.

beginner

Explain Forward compatibility in Kafka schemas.

Old schema can read data written with the new schema version, so consumers using the old schema can read new data.

intermediate

What is Full compatibility?

It means the schema is both backward and forward compatible, so both old and new consumers can read data from either schema version.

Which compatibility rule allows new consumers to read old data but not vice versa?

A Backward compatibility

B Forward compatibility

C Full compatibility

D None compatibility

Backward compatibility means new schema can read old data, but old consumers may not read new data.

If a schema change breaks both backward and forward compatibility, which compatibility setting should be used?

A Backward

B Forward

C Full

D None

None compatibility means no compatibility checks are enforced, allowing any schema changes.

What does full compatibility guarantee?

A Only new consumers can read old data

B Both old and new consumers can read data from either schema version

C Only old consumers can read new data

D No compatibility between schema versions

Full compatibility means both backward and forward compatibility are ensured.

Which schema compatibility rule is the strictest?

A Full

B Forward

C None

D Backward

Full compatibility requires both backward and forward compatibility, making it the strictest.

Adding a new optional field to a schema is usually compatible with which rule?

A Backward compatibility

B Forward compatibility

C Full compatibility

D None compatibility

Adding an optional field is both backward and forward compatible, so it fits full compatibility.

Describe the differences between backward, forward, and full schema compatibility in Kafka.

Think about who can read data written by whom.

Explain why schema compatibility is important in Kafka data pipelines.

Consider what happens if schema changes break data reading.