Apache Avro provides a way to serialize data using JSON schemas. These schema files are always present with the data, allowing developers to ship both the data and its structure to any application that may need it.
Because of this data can be read and written at very high speeds, while also making it available for further processing to other programming languages that can handle a basic JSON file.
Because JSON can handle quite complicated nested structures, the data can also be in a complex form as well.
Apache Avro is quite an useful tool, especially for RPC operations where leaving a schema file on the client and the server can improve data queries times and inter-connectivity.
Current Avro APIs are available for:
- Java
- C
- C++
- PHP
- Perl
- Ruby
- Python
What is new in this release:
- New Features:
- Added Perl implementation to Avro
- Java: Schema Validation utilities
- Support for DECIMAL type
- MultipleInputs equivalent for Avro MR
- Permit promotions between string and bytes
What is new in version 1.7.7:
- New Features:
- Added Perl implementation to Avro
- Java: Schema Validation utilities
- Support for DECIMAL type
- MultipleInputs equivalent for Avro MR
- Permit promotions between string and bytes
What is new in version 1.7.2:
- Added a column-major file format.
What is new in version 1.6.0:
- Added a library of standard schemas.
What is new in version 1.5.2:
- Allow interdependancies across IDL schema imports.
- Cache hash codes in Schema and Field.
- Python implementation of mapreduce connector.
What is new in version 1.5.1:
- Bugfix release.
What is new in version 1.2.0:
- Fix multi-threading race condition when threads share schema objects.
- Record objects from different packages is not supported with the reflection API.
- Use an existing unit test framework for C++ (boost).
- C++ version is using wrong endian for varints.
- Avro code generation should never cast an element to Object.
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