Skip to content


The BJData format was derived from and improved upon Universal Binary JSON(UBJSON) specification (Draft 12). Specifically, it introduces an optimized array container for efficient storage of N-dimensional packed arrays (ND-arrays); it also adds 4 new type markers - [u] - uint16, [m] - uint32, [M] - uint64 and [h] - float16 - to unambigiously map common binary numeric types; furthermore, it uses little-endian (LE) to store all numerics instead of big-endian (BE) as in UBJSON to avoid unnecessary conversions on commonly available platforms.

Compared to other binary-JSON-like formats such as MessagePack and CBOR, both BJData and UBJSON demonstrate a rare combination of being both binary and quasi-human-readable. This is because all semantic elements in BJData and UBJSON, including the data-type markers and name/string types are directly human-readable. Data stored in the BJData/UBJSON format are not only compact in size, fast to read/write, but also can be directly searched or read using simple processing.


The library uses the following mapping from JSON values types to BJData types according to the BJData specification:

JSON value type value/range BJData type marker
null null null Z
boolean true true T
boolean false false F
number_integer -9223372036854775808..-2147483649 int64 L
number_integer -2147483648..-32769 int32 l
number_integer -32768..-129 int16 I
number_integer -128..127 int8 i
number_integer 128..255 uint8 U
number_integer 256..32767 int16 I
number_integer 32768..65535 uint16 u
number_integer 65536..2147483647 int32 l
number_integer 2147483648..4294967295 uint32 m
number_integer 4294967296..9223372036854775807 int64 L
number_integer 9223372036854775808..18446744073709551615 uint64 M
number_unsigned 0..127 int8 i
number_unsigned 128..255 uint8 U
number_unsigned 256..32767 int16 I
number_unsigned 32768..65535 uint16 u
number_unsigned 65536..2147483647 int32 l
number_unsigned 2147483648..4294967295 uint32 m
number_unsigned 4294967296..9223372036854775807 int64 L
number_unsigned 9223372036854775808..18446744073709551615 uint64 M
number_float any value float64 D
string with shortest length indicator string S
array see notes on optimized format/ND-array array [
object see notes on optimized format map {

Complete mapping

The mapping is complete in the sense that any JSON value type can be converted to a BJData value.

Any BJData output created by to_bjdata can be successfully parsed by from_bjdata.

Size constraints

The following values can not be converted to a BJData value:

  • strings with more than 18446744073709551615 bytes (theoretical)

Unused BJData markers

The following markers are not used in the conversion:

  • Z: no-op values are not created.
  • C: single-byte strings are serialized with S markers.

NaN/infinity handling

If NaN or Infinity are stored inside a JSON number, they are serialized properly. This behavior differs from the dump() function which serializes NaN or Infinity to null.


A breaking difference between BJData and UBJSON is the endianness of numerical values. In BJData, all numerical data types (integers UiuImlML and floating-point values hdD) are stored in the little-endian (LE) byte order as opposed to big-endian as used by UBJSON. To adopt LE to store numeric records avoids unnecessary byte swapping on most modern computers where LE is used as the default byte order.

Optimized formats

The optimized formats for containers are supported: Parameter use_size adds size information to the beginning of a container and removes the closing marker. Parameter use_type further checks whether all elements of a container have the same type and adds the type marker to the beginning of the container. The use_type parameter must only be used together with use_size = true.

Note that use_size = true alone may result in larger representations - the benefit of this parameter is that the receiving side is immediately informed on the number of elements of the container.

ND-array optimized format

BJData extends UBJSON's optimized array size marker to support ND-array of uniform numerical data types (referred to as the packed array). For example, 2-D uint8 integer array [[1,2],[3,4],[5,6]] that can be stored as nested optimized array in UBJSON [ [$U#i2 1 2 [$U#i2 3 4 [$U#i2 5 6 ], can be further compressed in BJData and stored as [$U#[$i#i2 2 3 1 2 3 4 5 6 or [$U#[i2 i3] 1 2 3 4 5 6.

In order to maintain the type and dimension information of an ND-array, when this library parses a BJData ND-array via from_bjdata, it converts the data into a JSON object, following the annotated array format as defined in the JData specification (Draft 3). For example, the above 2-D uint8 array can be parsed and accessed as

    "_ArrayType_": "uint8",
    "_ArraySize_": [2,3],
    "_ArrayData_": [1,2,3,4,5,6]

In the reversed direction, when to_bjdata detects a JSON object in the above form, it automatically converts such object into a BJData ND-array to generate compact output. The only exception is that when the 1-D dimensional vector stored in "_ArraySize_" contains a single integer, or two integers with one being 1, a regular 1-D optimized array is generated.

The current version of this library has not yet supported automatic recognition and conversion from a nested JSON array input to a BJData ND-array.

Restrictions in optimized data types for arrays and objects

Due to diminished space saving, hampered readability, and increased security risks, in BJData, the allowed data types following the $ marker in an optimized array and object container are restricted to non-zero-fixed-length data types. Therefore, the valid optimized type markers can only be one of UiuImlMLhdDC. This also means other variable ([{SH) or zero-length types (TFN) can not be used in an optimized array or object in BJData.

Binary values

If the JSON data contains the binary type, the value stored is a list of integers, as suggested by the BJData documentation. In particular, this means that serialization and the deserialization of a JSON containing binary values into BJData and back will result in a different JSON object.

#include <iostream>
#include <iomanip>
#include <nlohmann/json.hpp>

using json = nlohmann::json;

// function to print BJData's diagnostic format
void print_byte(uint8_t byte)
    if (32 < byte and byte < 128)
        std::cout << (char)byte;
        std::cout << (int)byte;

int main()
    // create a JSON value
    json j = R"({"compact": true, "schema": false})"_json;

    // serialize it to BJData
    std::vector<std::uint8_t> v = json::to_bjdata(j);

    // print the vector content
    for (auto& byte : v)
    std::cout << std::endl;

    // create an array of numbers
    json array = {1, 2, 3, 4, 5, 6, 7, 8};

    // serialize it to BJData using default representation
    std::vector<std::uint8_t> v_array = json::to_bjdata(array);
    // serialize it to BJData using size optimization
    std::vector<std::uint8_t> v_array_size = json::to_bjdata(array, true);
    // serialize it to BJData using type optimization
    std::vector<std::uint8_t> v_array_size_and_type = json::to_bjdata(array, true, true);

    // print the vector contents
    for (auto& byte : v_array)
    std::cout << std::endl;

    for (auto& byte : v_array_size)
    std::cout << std::endl;

    for (auto& byte : v_array_size_and_type)
    std::cout << std::endl;




The library maps BJData types to JSON value types as follows:

BJData type JSON value type marker
no-op no value, next value is read N
null null Z
false false F
true true T
float16 number_float h
float32 number_float d
float64 number_float D
uint8 number_unsigned U
int8 number_integer i
uint16 number_unsigned u
int16 number_integer I
uint32 number_unsigned m
int32 number_integer l
uint64 number_unsigned M
int64 number_integer L
string string S
char string C
array array (optimized values are supported) [
ND-array object (in JData annotated array format) [$.#[.
object object (optimized values are supported) {

Complete mapping

The mapping is complete in the sense that any BJData value can be converted to a JSON value.

#include <iostream>
#include <iomanip>
#include <nlohmann/json.hpp>

using json = nlohmann::json;

int main()
    // create byte vector
    std::vector<std::uint8_t> v = {0x7B, 0x69, 0x07, 0x63, 0x6F, 0x6D, 0x70, 0x61,
                                   0x63, 0x74, 0x54, 0x69, 0x06, 0x73, 0x63, 0x68,
                                   0x65, 0x6D, 0x61, 0x69, 0x00, 0x7D

    // deserialize it with BJData
    json j = json::from_bjdata(v);

    // print the deserialized JSON value
    std::cout << std::setw(2) << j << std::endl;


  "compact": true,
  "schema": 0

Last update: May 17, 2022
Back to top