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  1. Stackups
  2. Application & Data
  3. Frameworks
  4. Serialization Frameworks
  5. Avro vs MessagePack

Avro vs MessagePack

OverviewComparisonAlternatives

Overview

MessagePack
MessagePack
Stacks51
Followers79
Votes1
GitHub Stars7.3K
Forks521
Avro
Avro
Stacks419
Followers178
Votes0

Avro vs MessagePack: What are the differences?

Introduction

Avro and MessagePack are both data serialization formats commonly used in the field of computer science. While they serve a similar purpose of converting data into a binary format, there are key differences between the two that make them suitable for different use cases.

  1. Data Schema Definition: Avro requires a schema to be defined before serializing the data, using a JSON format. This allows for strong typing and data validation at the expense of increased complexity. On the other hand, MessagePack does not require a schema definition and is schema-less, making it more flexible but sacrificing data validation.

  2. Interoperability and Language Support: Avro is a language-neutral format and provides support for multiple programming languages through code generation from the defined schema. This makes it easier to integrate Avro with different systems using different programming languages. In contrast, MessagePack focuses on being lightweight and provides a simple binary format, which offers broad interoperability but may lack the same level of language support as Avro.

  3. Data Storage Efficiency: Avro includes the schema information within the serialized data, which results in a slightly larger serialized size compared to MessagePack. This may affect data storage efficiency, especially when working with a large dataset. On the other hand, MessagePack does not include schema information, resulting in a more compact serialized size and potentially better storage efficiency.

  4. Data Transformation and Compatibility: Avro supports evolving schemas, allowing for forward and backward compatibility when the schema changes over time. This means that Avro can handle data transformation and manipulation more easily, making it suitable for applications with evolving data structures. MessagePack, being schema-less, does not have built-in support for schema evolution and may require additional handling and versioning mechanisms.

  5. Performance and Speed: Both Avro and MessagePack are designed to be fast and efficient serialization formats. However, Avro's emphasis on schema validation and compatibility may introduce some overhead in terms of performance compared to MessagePack, which has a simpler and more lightweight binary format.

  6. Community and Ecosystem: Avro has gained significant adoption and has a broader ecosystem with various tools, libraries, and support available. MessagePack, while also having its own community, may have a smaller ecosystem compared to Avro.

In summary, Avro and MessagePack have key differences in their data schema definition, interoperability, storage efficiency, data transformation capability, performance, and community support. The choice between the two depends on the specific requirements and constraints of the application at hand.

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Detailed Comparison

MessagePack
MessagePack
Avro
Avro

It is an efficient binary serialization format. It lets you exchange data among multiple languages like JSON. But it's faster and smaller. Small integers are encoded into a single byte, and typical short strings require only one extra byte in addition to the strings themselves.

It is a row-oriented remote procedure call and data serialization framework developed within Apache's Hadoop project. It uses JSON for defining data types and protocols, and serializes data in a compact binary format.

Binary serialization format; Exchange data among multiple languages ; Faster and smaller
Schema Evolution; Code Generation; Untagged Data; Language Support
Statistics
GitHub Stars
7.3K
GitHub Stars
-
GitHub Forks
521
GitHub Forks
-
Stacks
51
Stacks
419
Followers
79
Followers
178
Votes
1
Votes
0
Pros & Cons
Pros
  • 1
    Lightweight
No community feedback yet
Integrations
Redis
Redis
Ruby
Ruby
Fluentd
Fluentd
Haskell
Haskell
Java
Java
PHP
PHP
Python
Python
Ruby
Ruby
C++
C++
C#
C#

What are some alternatives to MessagePack, Avro?

Protobuf

Protobuf

Protocol buffers are Google's language-neutral, platform-neutral, extensible mechanism for serializing structured data – think XML, but smaller, faster, and simpler.

Apache Thrift

Apache Thrift

The Apache Thrift software framework, for scalable cross-language services development, combines a software stack with a code generation engine to build services that work efficiently and seamlessly between C++, Java, Python, PHP, Ruby, Erlang, Perl, Haskell, C#, Cocoa, JavaScript, Node.js, Smalltalk, OCaml and Delphi and other languages.

Serde

Serde

It is a framework for serializing and deserializing Rust data structures efficiently and generically. The ecosystem consists of data structures that know how to serialize and deserialize themselves along with data formats that know how to serialize and deserialize other things. It provides the layer by which these two groups interact with each other, allowing any supported data structure to be serialized and deserialized using any supported data format.

Sonic

Sonic

It is a blazingly fast JSON serializing & deserializing library, accelerated by JIT (just-in-time compiling) and SIMD (single-instruction-multiple-data).

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