Avro
Apache Avro is a language-independent data serialization system that uses schemas to encode structured data, commonly in compact binary or JSON form.
Kafka Streams in Action, Second Edition
Apache Avro is a data serialization system that uses schemas and supports language-independent serialization, code generation, and schema evolution.
- How it is used
- Enforces event-data contracts between Kafka producers and consumers through registered schemas and integrated serializers.
- How deep it goes
- Explains JSON record schemas, generated Java objects, serializer configuration, and specific versus generic consumer records; defers compatibility details.
- Examples
- Uses an Avengers schema and generated AvengerAvro objects, including a Black Widow event sent to and read from Kafka.
- What you can do after
- Apply it via KafkaAvroSerializer, KafkaAvroDeserializer, Schema Registry, and generated Java records.
Read how Kafka Streams in Action, Second Edition explains Avro →
Kafka for Architects
Avro is a data serialization system that represents structured records with schemas and a compact binary encoding.
- How it is used
- Defines language-independent event contracts and compact serialized data for Kafka-based customer events.
- How deep it goes
- Explains schema components, compact encoding, generated versus dynamic access, and registry-based serialization without an end-to-end implementation walkthrough.
- Examples
- Uses a Client record schema, an externally referenced user-profile schema, and Kafka producer and consumer configurations.
- What you can do after
- Apply it via Avro schemas and KafkaAvroSerializer to encode Kafka messages and maintain externally referenced event contracts.
Apache Kafka in Action
Avro is a schema-based data serialization system that encodes structured data in a compact binary format.
- How it is used
- Provides compact, schema-governed messages for Kafka topics whose data must remain interpretable across consumers and schema versions.
- How deep it goes
- Explains binary encoding, self-describing messages, schema size trade-offs, registry identifiers, and compatibility, but not producer implementation.
- Examples
- Uses a product record with typed fields, an optional origin value, binary payload sizing, and schema IDs in Kafka messages.
- What you can do after
- Evaluate Avro deployments by balancing compact payloads, readable schemas, registry overhead, and compatibility across evolving consumers.
Related concepts
- schema registryused by · A schema registry is a service that stores, versions, and provides schemas for structured data, often validating compatibility between schema versions.
- JSONuses · JSON is a standardized, language-independent text format for representing structured data using objects, arrays, strings, numbers, Boolean values, and null.
- KafkaAvroSerializerused by · KafkaAvroSerializer is a Kafka serializer that encodes Avro records and communicates with Schema Registry to obtain their schemas.
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