apache/fory

Apache Fory™ is a blazingly fast multi-language serialization framework for idiomatic domain objects, schema IDL, and cross-language data exchange.

https://fory.apache.org

Why Fory

Fory is built for fast, compact serialization across languages and implementations. It works with idiomatic objects in each language, supports shared schemas when you need a contract, and preserves object features such as shared and circular references.

• Efficient Cross-Language Encoding: Exchange payloads across supported languages with compact binary encoding, metadata packing, schema evolution, shared/circular references, and polymorphic runtime types.
• Domain Objects First: Serialize Java classes, Python dataclasses, Go structs, Rust/C++ structs, and generated or annotated model types directly. Preserve shared and circular references when object identity matters.
• Reference-Aware Schema IDL: Support shared and circular references directly in the schema, alongside numbers, strings, lists, maps, arrays, enums, structs, and unions. Define schemas once, then generate native domain objects for each language without forcing wrapper types into user code.
• Optimized Implementations: Java JIT serializers and generated/static serializers in other language implementations keep hot paths fast and payloads compact.
• Language And Platform Support: Java, Python, C++, Go, Rust, JavaScript/TypeScript, C#, Swift, Dart, Scala, and Kotlin, including GraalVM native image, Android, Dart VM/Flutter/web, and Node.js/browser JavaScript.

For same-language workloads, Fory provides native serialization modes that support broader language-specific object models:

• Java Native Serialization: A high-performance replacement for JDK serialization, Hessian, Kryo, and FST in Java-only systems. It supports JDK custom serialization semantics.
• Python Native Serialization: A faster and more compact replacement for pickle and cloudpickle in Python-only systems. It supports classes, modules, functions, and custom object state, with fine-grained deserialization controls through DeserializationPolicy.

Fory also provides specialized formats for other data-processing requirements:

• Row Format: Read fields, arrays, and nested values without rebuilding complete objects, with zero-copy access and partial reads.
• Fory JSON: A Java JSON serialization framework built for maximum throughput through runtime-generated codecs and optimized readers and writers. Supports Java 8 and later on standard JDKs, GraalVM native images, and Android, including Java 17 records.

Performance

Benchmarks show Fory delivering higher throughput and smaller serialized payloads than common serialization frameworks on representative workloads. Java has the broadest comparison set; the other charts show language-specific results across supported languages.

Java Benchmarks

In Java serialization benchmarks, Fory reaches up to 170x the throughput of JDK serialization on selected workloads.

Python Benchmarks

Rust Benchmarks

Benchmarks for C++, Go, JavaScript/TypeScript, C#, Swift, and Dart

C++ Benchmarks

Go Benchmarks

JavaScript/TypeScript Benchmarks

C# Benchmarks

Swift Benchmarks

Dart Benchmarks

Installation

Pick your language and run the package-manager command, or paste the dependency block into your build file.

Java

Maven:

<dependency>
  <groupId>org.apache.fory</groupId>
  <artifactId>fory-core</artifactId>
  <version>1.5.0</version>
</dependency>

Gradle:

implementation "org.apache.fory:fory-core:1.5.0"

On JDK25+, opening java.lang.invoke to Fory core is also recommended. It avoids the current-JDK Unsafe fallback and is required when Unsafe access is disabled or unavailable, including with --sun-misc-unsafe-memory-access=deny. Use ALL-UNNAMED when Fory is on the classpath:

--add-opens=java.base/java.lang.invoke=ALL-UNNAMED

Use the Fory core module name when Fory is on the module path:

--add-opens=java.base/java.lang.invoke=org.apache.fory.core

Scala

sbt:

libraryDependencies += "org.apache.fory" %% "fory-scala" % "1.5.0"

Kotlin

Gradle:

implementation("org.apache.fory:fory-kotlin:1.5.0")

Maven:

<dependency>
  <groupId>org.apache.fory</groupId>
  <artifactId>fory-kotlin</artifactId>
  <version>1.5.0</version>
</dependency>

Python

pip install pyfory

For row-format support:

pip install "pyfory[format]"

Rust

Cargo.toml:

[dependencies]
fory = "1.5.0"

C++

CMake:

include(FetchContent)
FetchContent_Declare(
  fory
  GIT_REPOSITORY https://github.com/apache/fory.git
  GIT_TAG v1.5.0
  SOURCE_SUBDIR cpp
)
FetchContent_MakeAvailable(fory)
target_link_libraries(my_app PRIVATE fory::serialization)

Bazel:

# MODULE.bazel
bazel_dep(name = "fory", version = "1.5.0")
git_override(module_name = "fory", remote = "https://github.com/apache/fory.git", commit = "v1.5.0")

# BUILD
deps = ["@fory//cpp/fory/serialization:fory_serialization"]

When building C++ with MSVC, enable the conforming preprocessor option /Zc:preprocessor; see the C++ installation guide for setup details.

See the C++ installation guide for complete CMake, Bazel, and source-build details.

Go

go get github.com/apache/fory/go/fory

JavaScript/TypeScript

npm install @apache-fory/core

For the Node.js string fast path:

npm install @apache-fory/core @apache-fory/hps

C#

dotnet add package Apache.Fory --version 1.5.0

Dart

dart pub add fory:^1.5.0
dart pub add dev:build_runner

Swift

Add Fory to Package.swift:

dependencies: [
  .package(url: "https://github.com/apache/fory.git", exact: "1.5.0")
],
targets: [
  .target(
    name: "YourTarget",
    dependencies: [.product(name: "Fory", package: "fory")]
  )
]

See the Swift guide for generated serializer setup.

Development From Source

See docs/development/index.md.

Snapshots for Java, Scala, and Kotlin are available from https://repository.apache.org/snapshots/ with the matching -SNAPSHOT version.

Choose a Serialization Format

For Java, Scala, Kotlin, Python, C++, Go, and Rust, use native mode for same-language traffic. It avoids xlang's cross-language type mapping and metadata constraints, stays closer to each language's native type system, and supports broader language-specific object graphs. Use it when both producer and consumer are in the same language family and you want the native object model rather than a portable cross-language schema.

For Java/JVM-only systems, native mode is the replacement path for JDK serialization, Kryo, FST, Hessian, and Java-only Protocol Buffers payloads. For Python-only systems, native mode is the replacement path for pickle and cloudpickle.

Compatible mode is Fory's schema-evolution mode. It writes the metadata readers and writers need to tolerate schema differences. It is the default for xlang mode and native mode in implementations that expose the option.

Use compatible mode when services deploy independently or when fields may be added or deleted over time. Set compatible mode to false only when every reader and writer always uses the same schema and you want faster serialization and smaller size. For xlang payloads, set compatible mode to false only after verifying that every language uses the same schema, or when native types are generated from Fory schema IDL.

For xlang, all peers must agree on type identity. Name-based registration is easier to read in examples. Numeric IDs are smaller and faster, but they require coordination across every reader and writer.

Cross-Language Serialization

Xlang mode writes the cross-language Fory wire format. Bytes produced by one language implementation can be read by another when every peer uses the same type identity, compatible mode setting, and field schema.

Java

import org.apache.fory.Fory;

public class Example {
  public static class Person {
    public String name;
    public int age;
  }

  public static void main(String[] args) {
    Fory fory = Fory.builder().withXlang(true).build();
    fory.register(Person.class, "example.Person");

    Person person = new Person();
    person.name = "Alice";
    person.age = 30;

    byte[] bytes = fory.serialize(person);
    Person decoded = (Person) fory.deserialize(bytes);
    System.out.println(decoded.name);
  }
}

Python

from dataclasses import dataclass

import pyfory

@dataclass
class Person:
    name: str
    age: pyfory.Int32

fory = pyfory.Fory(xlang=True)
fory.register_type(Person, name="example.Person")

data = fory.serialize(Person("Alice", 30))
person = fory.deserialize(data)
print(person.name)

Go

package main

import (
    "fmt"

    "github.com/apache/fory/go/fory"
)

type Person struct {
    Name string
    Age  int32
}

func main() {
    f := fory.New(fory.WithXlang(true))
    if err := f.RegisterStructByName(Person{}, "example.Person"); err != nil {
        panic(err)
    }

    data, _ := f.Serialize(&Person{Name: "Alice", Age: 30})
    var person Person
    if err := f.Deserialize(data, &person); err != nil {
        panic(err)
    }
    fmt.Println(person.Name)
}

Rust

use fory::{Error, Fory, ForyStruct};

#[derive(ForyStruct, Debug, PartialEq)]
struct Person {
    name: String,
    age: i32,
}

fn main() -> Result<(), Error> {
    let mut fory = Fory::builder().xlang(true).build();
    fory.register_by_name::<Person>("example.Person")?;

    let bytes = fory.serialize(&Person {
        name: "Alice".to_string(),
        age: 30,
    })?;
    let person: Person = fory.deserialize(&bytes)?;
    println!("{}", person.name);
    Ok(())
}

C++

#include "fory/serialization/fory.h"
#include <cstdint>
#include <iostream>
#include <string>

using namespace fory::serialization;

struct Person {
  std::string name;
  int32_t age;
};
FORY_STRUCT(Person, name, age);

int main() {
  auto fory = Fory::builder().xlang(true).build();
  fory.register_struct<Person>("example.Person");

  auto bytes = fory.serialize(Person{"Alice", 30}).value();
  Person person = fory.deserialize<Person>(bytes).value();
  std::cout << person.name << std::endl;
}

JavaScript/TypeScript

import Fory, { Type } from "@apache-fory/core";

const personType = Type.struct(
  { typeName: "example.Person" },
  {
    name: Type.string(),
    age: Type.int32(),
  },
);

const fory = new Fory();
const { serialize, deserialize } = fory.register(personType);

const bytes = serialize({ name: "Alice", age: 30 });
const person = deserialize(bytes);
console.log(person.name);

C#

using Apache.Fory;

[ForyStruct]
public sealed class Person
{
    public string Name { get; set; } = string.Empty;
    public int Age { get; set; }
}

Fory fory = Fory.Builder().Build();
fory.Register<Person>("example", "Person");

byte[] bytes = fory.Serialize(new Person { Name = "Alice", Age = 30 });
Person person = fory.Deserialize<Person>(bytes);
Console.WriteLine(person.Name);

C# always writes the xlang frame header, so there is no separate xlang builder flag.

Dart

import 'package:fory/fory.dart';

part 'person.fory.dart';

@ForyStruct()
class Person {
  Person();

  String name = '';

  @ForyField(type: Int32Type())
  int age = 0;
}

void main() {
  final fory = Fory();
  PersonFory.register(
    fory,
    Person,
    name: 'example.Person',
  );

  final bytes = fory.serialize(Person()
    ..name = 'Alice'
    ..age = 30);
  final person = fory.deserialize<Person>(bytes);
  print(person.name);
}

Dart uses the xlang wire format directly. Generate the companion file before running:

dart run build_runner build

Swift

import Fory

@ForyStruct
struct Person {
    var name: String = ""
    var age: Int32 = 0
}

let fory = Fory()
try fory.register(Person.self, name: "example.Person")

let bytes = try fory.serialize(Person(name: "Alice", age: 30))
let person: Person = try fory.deserialize(bytes)
print(person.name)

Scala

import org.apache.fory.scala.ForyScala

case class Person(name: String, age: Int)

val fory = ForyScala.builder().withXlang(true).build()
fory.register(classOf[Person], "example.Person")

val bytes = fory.serialize(Person("Alice", 30))
val person = fory.deserialize(bytes).asInstanceOf[Person]
println(person.name)

Kotlin

import org.apache.fory.kotlin.ForyKotlin

data class Person(val name: String, val age: Int)

fun main() {
    val fory = ForyKotlin.builder().withXlang(true).build()
    fory.register(Person::class.java, "example.Person")

    val bytes = fory.serialize(Person("Alice", 30))
    val person = fory.deserialize(bytes) as Person
    println(person.name)
}

For shared/circular references, polymorphism, numeric IDs versus names, and type-mapping rules, see the cross-language guide and type mapping specification.

Native Serialization

Use native mode when the writer and reader are in the same language. It is optimized for each language's native type system and can cover language-specific types, object graphs, and framework-replacement cases that xlang mode keeps out of the portable wire format. The languages below expose an explicit xlang=false or native-mode setting; implementations without that switch stay on their documented default path.

Choose Java native mode for Java/JVM-only replacements of JDK serialization, Kryo, FST, Hessian, or Java-only Protocol Buffers payloads. Choose Python native mode when replacing pickle or cloudpickle for Python-only payloads.

Keep class/type registration enabled for untrusted input. See the language guides for language-specific security and compatibility settings.

Java

Fory fory = Fory.builder()
    .withXlang(false)
    .requireClassRegistration(true)
    .build();
// Register, serialize, and deserialize as in the xlang example above.

Python

fory = pyfory.Fory(xlang=False, ref=True)
# Register, serialize, and deserialize as in the xlang example above.

Go

f := fory.New(fory.WithXlang(false))
// Register, serialize, and deserialize as in the xlang example above.

Rust

let mut fory = Fory::builder().xlang(false).build();
// Register, serialize, and deserialize as in the xlang example above.

C++

auto fory = Fory::builder().xlang(false).build();
// Register, serialize, and deserialize as in the xlang example above.

Scala

import org.apache.fory.scala.ForyScala

val fory = ForyScala.builder()
  .withXlang(false)
  .requireClassRegistration(true)
  .build()
// Register, serialize, and deserialize as in the xlang example above.

Kotlin

import org.apache.fory.kotlin.ForyKotlin

val fory = ForyKotlin.builder()
    .withXlang(false)
    .requireClassRegistration(true)
    .build()
// Register, serialize, and deserialize as in the xlang example above.

Schema IDL

Fory IDL is Fory's schema-first path for shared data models. Use it when multiple languages need one explicit contract, stable field identities, and generated native domain objects instead of manually coordinating equivalent types in every implementation.

The schema supports primitive values, nullable fields, lists, maps, dense arrays, enums, messages, unions, imports, and first-class shared or circular references. The compiler generates idiomatic models and Fory integration for Java, Python, C++, Go, Rust, JavaScript/TypeScript, C#, Swift, Dart, Scala, and Kotlin. It can also generate Fory-backed gRPC service companions for supported languages.

Install the compiler from PyPI:

pip install fory-compiler

Define the shared model in tree.fdl:

package tree;

message TreeNode {
    string id = 1;
    string name = 2;

    list<ref TreeNode> children = 3;
    ref(weak=true) TreeNode parent = 4; // back-pointer
}

Generate native models for the languages used by your application:

foryc tree.fdl --lang java,python,rust --output ./generated

Generated types use each language's normal classes, structs, dataclasses, annotations, macros, or registration helpers, so application code works with native domain objects while all peers share the same Fory schema. See the Fory IDL and compiler guide for the complete type system, language-specific output options, schema evolution, and gRPC generation.

Row Format

Row format is for random access and partial reads. These examples encode an object with an integer array field, then read one array element from the binary row without rebuilding the object.

Python

from dataclasses import dataclass
from typing import List

import pyfory

@dataclass
class User:
    id: pyfory.Int32
    name: str
    scores: List[pyfory.Int32]

encoder = pyfory.encoder(User)
binary = encoder.to_row(User(1, "Alice", [98, 100, 95])).to_bytes()

row = pyfory.RowData(encoder.schema, binary)
print(row.name)
print(row.scores[1])

Java

public class User {
  public int id;
  public String name;
  public int[] scores;
}

RowEncoder<User> encoder = Encoders.bean(User.class);

User user = new User();
user.id = 1;
user.name = "Alice";
user.scores = new int[] {98, 100, 95};

BinaryRow row = encoder.toRow(user);

Schema schema = encoder.schema();
Schema.StringField nameField = schema.stringField("name");
Schema.ArrayField scoresField = schema.arrayField("scores");

String name = nameField.get(row);
ArrayData scores = scoresField.get(row);
int secondScore = scores.getInt32(1);

For Java imports, nested structs, arrays/maps, Arrow integration, and partial deserialization, see the Java row-format guide, Python row-format guide, C++ row-format guide, Rust row-format guide, and row-format specification.

Fory JSON

Fory JSON is a thread-safe JSON serialization framework for Java, extensively optimized for maximum performance across JSON encoding, decoding, and Java object mapping. It supports Java 8 and later on standard JDKs, GraalVM native images, and Android, with Java records supported on Java 17 and later.

Performance

The benchmark compares fory-json with Jackson and Gson using String and UTF-8 byte APIs. The String group excludes UTF-8 conversion. Gson's byte results include its required String/UTF-8 conversion. Higher throughput is better. See the full benchmark report for more details.

Add Fory JSON to your project:

Maven

<dependency>
  <groupId>org.apache.fory</groupId>
  <artifactId>fory-json</artifactId>
  <version>1.5.0</version>
</dependency>

Gradle

implementation "org.apache.fory:fory-json:1.5.0"

Keep all Fory modules in the same application on the same version.

Quick Start

Build one ForyJson instance and reuse it across threads:

import org.apache.fory.json.ForyJson;

public final class JsonExample {
  private static final ForyJson JSON = ForyJson.builder().build();

  public static final class User {
    public long id;
    public String name;

    public User() {}

    public User(long id, String name) {
      this.id = id;
      this.name = name;
    }
  }

  public static void main(String[] args) {
    User input = new User(7, "Alice");

    String text = JSON.toJson(input);
    User fromText = JSON.fromJson(text, User.class);

    byte[] bytes = JSON.toJsonBytes(input);
    User fromBytes = JSON.fromJson(bytes, User.class);

    System.out.println(fromText.name + " / " + fromBytes.name);
  }
}

Start with the Fory JSON module README, then use the Fory JSON documentation for the complete mapping, annotation, codec, security, and platform guides.

Documentation

User Guides

Specifications

Community

• Slack workspace
• @ApacheFory on X
• GitHub issues
• Apache Fory mailing lists for development discussion

Contributing

Read CONTRIBUTING.md and docs/development/index.md before sending pull requests. Bug reports, docs fixes, tests, benchmarks, and implementation improvements are welcome.

License

Apache Fory™ is licensed under the Apache License 2.0.