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Apache Thrift vs Avro: What are the differences?

  1. Key Difference 1: Data Serialization Apache Thrift and Avro have different approaches to data serialization. Thrift uses a binary format that is optimized for efficient data transport, making it suitable for high-performance use cases. On the other hand, Avro uses a compact binary encoding that includes the schema with the data, making it self-describing and providing compatibility between different versions of schemas.

  2. Key Difference 2: Schema Evolution When it comes to schema evolution, Apache Thrift and Avro differ in their capabilities. Thrift relies on explicit versioning and requires both the client and the server to use compatible versions of the schema. Any changes to the schema necessitate updating and redeploying all related services. Avro, on the other hand, supports schema evolution, allowing new fields to be added and older fields to be read with their default values, without requiring a corresponding change in the client code.

  3. Key Difference 3: Language Support Apache Thrift and Avro also differ in terms of language support. Thrift provides support for a broader range of languages, including C++, Java, Python, and more. Avro, on the other hand, primarily focuses on Java and a limited set of languages, which may be a consideration when choosing the appropriate technology stack for a project.

  4. Key Difference 4: Performance In terms of performance, Apache Thrift and Avro exhibit different characteristics. Thrift is generally considered to have better performance due to its compact binary encoding and code generation, which eliminates the need for reflection. Avro, while still performant, incurs the overhead of including schema information with the data, which adds some additional size and processing cost.

  5. Key Difference 5: Schema Registry Another key difference between Apache Thrift and Avro is the presence of a schema registry. Avro typically utilizes a schema registry, which provides centralized schema management, versioning, and compatibility checks. Thrift, on the other hand, does not have a built-in schema registry, requiring manual coordination and version management between services.

  6. Key Difference 6: Ecosystem and Maturity In terms of ecosystem and maturity, Apache Thrift and Avro have some notable differences. Thrift has been around for a longer time, has a larger user base, and is backed by the Apache Software Foundation. It has a well-established ecosystem, including support for various protocols and frameworks. Avro, while also widely used, has a relatively smaller ecosystem and may have fewer resources available for certain use cases.

In summary, Apache Thrift and Avro differ in their approaches to data serialization, schema evolution, language support, performance, the presence of a schema registry, and their ecosystem and maturity. Choose Apache Thrift for optimized transport and better support across languages, or choose Avro for self-describing data, schema evolution, and compatibility between different schema versions.

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What is 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.

What is Avro?

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.

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What are some alternatives to Apache Thrift and Avro?
gRPC
gRPC is a modern open source high performance RPC framework that can run in any environment. It can efficiently connect services in and across data centers with pluggable support for load balancing, tracing, health checking...
Protobuf
Protocol buffers are Google's language-neutral, platform-neutral, extensible mechanism for serializing structured data – think XML, but smaller, faster, and simpler.
REST
An architectural style for developing web services. A distributed system framework that uses Web protocols and technologies.
GraphQL
GraphQL is a data query language and runtime designed and used at Facebook to request and deliver data to mobile and web apps since 2012.
JSON
JavaScript Object Notation is a lightweight data-interchange format. It is easy for humans to read and write. It is easy for machines to parse and generate. It is based on a subset of the JavaScript Programming Language.
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