avro-js vs avsc
Data Serialization Libraries
avro-jsavsc

Data Serialization Libraries

Data serialization libraries facilitate the encoding of data structures into a format suitable for storage or transmission. They are crucial in scenarios where data needs to be shared between different systems or stored efficiently. Avro is a popular serialization framework that provides a compact binary format and rich data structures, making it ideal for big data applications. Both 'avro-js' and 'avsc' are JavaScript implementations of the Avro specification, enabling developers to serialize and deserialize data in Avro format within Node.js and browser environments.

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avro-js72,2303,251170 kB1635 months agoApache-2.0
avsc01,376264 kB268 months agoMIT

Feature Comparison: avro-js vs avsc

Schema Support

  • avro-js:

    Avro-js supports basic schema definitions and allows for serialization and deserialization of data according to those schemas. However, it may not handle complex schema features as extensively as other libraries.

  • avsc:

    Avsc provides comprehensive support for Avro schemas, including complex types, unions, and default values. It allows for schema evolution, enabling developers to modify schemas while maintaining compatibility with existing data.

Performance

  • avro-js:

    Avro-js is designed for lightweight operations, making it suitable for applications where performance is critical but advanced features are not necessary. Its performance is generally good for simple use cases.

  • avsc:

    Avsc is optimized for performance and can handle larger datasets efficiently. It includes features like lazy loading of schemas and optimized serialization paths, making it suitable for high-performance applications.

Error Handling

  • avro-js:

    Error handling in avro-js is relatively straightforward, focusing on basic validation during serialization and deserialization. However, it may not provide detailed error reporting for complex scenarios.

  • avsc:

    Avsc offers robust error handling capabilities, including detailed error messages and validation checks. This makes it easier for developers to debug issues related to schema mismatches or data inconsistencies.

Community and Support

  • avro-js:

    Avro-js has a smaller community compared to avsc, which may result in fewer resources and examples available for troubleshooting and learning.

  • avsc:

    Avsc has a larger community and more extensive documentation, providing better support for developers. It also has more examples and use cases available, making it easier to find solutions to common problems.

Ease of Use

  • avro-js:

    Avro-js is designed with simplicity in mind, making it easy to get started with Avro serialization. Its API is straightforward, which is beneficial for developers who need quick implementations.

  • avsc:

    Avsc, while feature-rich, may have a steeper learning curve due to its extensive capabilities. However, once mastered, it provides powerful tools for working with Avro data.

How to Choose: avro-js vs avsc

  • avro-js:

    Choose 'avro-js' if you require a lightweight library that focuses on providing a simple API for Avro serialization and deserialization. It is particularly suited for projects where minimal overhead is desired and where you may not need extensive features beyond basic serialization.

  • avsc:

    Choose 'avsc' if you need a more feature-rich library that supports advanced Avro features such as schema evolution, complex data types, and better error handling. It is ideal for applications that require robust serialization capabilities and compatibility with various Avro data types.

README for avro-js

Avro-js

Pure JavaScript implementation of the Avro specification.

Features

  • Fast! Typically twice as fast as JSON with much smaller encodings.
  • Full Avro support, including recursive schemas, sort order, and evolution.
  • Serialization of arbitrary JavaScript objects via logical types.
  • Unopinionated 64-bit integer compatibility.
  • No dependencies, avro-js even runs in the browser.

Installation

$ npm install avro-js

avro-js is compatible with all versions of node.js since 0.11 and major browsers via browserify.

Documentation

See doc/ folder.

Examples

Inside a node.js module, or using browserify:

var avro = require('avro-js');
  • Encode and decode objects:

    // We can declare a schema inline:
    var type = avro.parse({
      name: 'Pet',
      type: 'record',
      fields: [
        {name: 'kind', type: {name: 'Kind', type: 'enum', symbols: ['CAT', 'DOG']}},
        {name: 'name', type: 'string'}
      ]
    });
    var pet = {kind: 'CAT', name: 'Albert'};
    var buf = type.toBuffer(pet); // Serialized object.
    var obj = type.fromBuffer(buf); // {kind: 'CAT', name: 'Albert'}
    
  • Generate random instances of a schema:

    // We can also parse a JSON-stringified schema:
    var type = avro.parse('{"type": "fixed", "name": "Id", "size": 4}');
    var id = type.random(); // E.g. Buffer([48, 152, 2, 123])
    
  • Check whether an object fits a given schema:

    // Or we can specify a path to a schema file (not in the browser):
    var type = avro.parse('./Person.avsc');
    var person = {name: 'Bob', address: {city: 'Cambridge', zip: '02139'}};
    var status = type.isValid(person); // Boolean status.
    
  • Get a readable stream of decoded records from an Avro container file (not in the browser):

    avro.createFileDecoder('./records.avro')
      .on('metadata', function (type) { /* `type` is the writer's type. */ })
      .on('data', function (record) { /* Do something with the record. */ });
    
  • Implement recursive schemata (due to lack of duck-typing):

      // example type: linked list with one long-int as element value
      const recursiveRecordType =  avro.parse({
        "type": "record",
        "name": "LongList",
        "fields" : [
          {"name": "value", "type": "long"},             
          {"name": "next", "type": ["null", "LongList"]} // optional next element via recursion
        ]
      });
    
      // will work
      const validRecursiveRecordDTO = {
        value: 1,
        next: {
          // no duck-typing support: from first nested level on the 
          // recursive type has to be explicitly specified.
          LongList: {
            value: 2,
            next: null
          }
        }
      };
      const serializedValid = recursiveRecordType.parse(validRecursiveRecordDTO);
      
    
      // will throw error
      const invalidRecursiveRecordDTO = {
        value: 1,
        next: {
            value: 2,
            next: null
        }
      };
      const serializedInvalid = recursiveRecordType.parse(invalidRecursiveRecordDTO);