What is Apache Avro?
Apache Avro is a data serialization system. It compresses and serializes data in a binary format, enabling efficient transmission between applications and processes. Avro is open-source and was first introduced by Doug Cutting, the creator of Hadoop. In contrast to other serialization methods, Avro is dynamic and makes schema evolution easier.
How does Apache Avro work?
Avro is a language-agnostic serialization system. It means it supports serialization in various programming languages, including Java, Python, Ruby, C++, and many others. The framework is composed of three parts:
- Schema: Avro uses schemas to define the type and structure of data. It is a JSON object that specifies the data structure and field names. The schema can be included in the data file or stored separately and linked later.
- Serialization: Avro serialization encodes the data into a compact binary format. It converts the data into an efficient, compressed, and splittable binary encoding that can be streamed efficiently.
- Deserialization: Deserialization reconstructs the original data from the byte stream.
Why is Apache Avro important?
Apache Avro is important because of its several advantages, including:
- Schema Evolution: With Avro's dynamic schema, it is easy to evolve the schema without breaking backward compatibility. It allows adding, removing, or changing fields to the schema without impacting the data consumers.
- Efficient Data Storage and Transmission: Avro's compact binary format enables fast data transmission and efficient storage. It is ideal for data processing and analytics operations that deal with large amounts of data.
- Language-agnostic: Avro is independent of any programming language or platform. It enables data serialization and deserialization in any language that supports it.
The most important Apache Avro use cases
Apache Avro is widely used in big data frameworks, including Apache Hadoop, Apache Spark, Apache Hive, and Apache Pig. It is also preferred for data storage, message passing, and data exchange in other distributed systems. Here are some of the most common use cases for Avro:
- Stream Processing: Avro is ideal for stream processing as it compresses and serializes data, making it easy to transmit through different message queues and distributed systems.
- Data Storage: Avro supports high-speed data storage and retrieval in distributed file systems. Avro files can be split or combined to enable efficient data processing.
- Data Exchange: Avro enables efficient data exchange between different systems and programming languages. It allows streaming of data between different applications and processes.
Some other technologies and terms that are related to Apache Avro include:
- Apache Thrift: Apache Thrift is a similar data serialization and communication framework.
- Protocol Buffers: Protocol Buffers is another lightweight and efficient serialization framework.
- Parquet: Parquet is an open-source columnar storage format that is widely used in big data frameworks.
Why Dremio users would be interested in Apache Avro?
Dremio is a data lakehouse platform that enables businesses to consolidate data lakes and data warehouses. Apache Avro is essential in creating data lakes as it enables efficient data storage, transfer, and processing. Dremio users can benefit from Avro's efficient and compact binary format for data storage and transmission in distributed systems. Avro's schema evolution feature also provides flexibility in evolving the schema without impacting data consumers.