gojsonq

Pros of gjson

• Faster performance, especially for large JSON files
• Supports a wider range of JSON operations, including JSON Lines and JSON Streaming
• More lightweight and focused on JSON parsing and querying

Cons of gjson

• Less flexible query syntax compared to gojsonq
• Lacks advanced features like aggregation and sorting
• No built-in support for writing or modifying JSON data

Code Comparison

gojsonq example:

result := gojsonq.New().File("data.json").
    From("users").
    Where("age", ">", 30).
    Select("name", "email").
    Get()

gjson example:

data, _ := ioutil.ReadFile("data.json")
result := gjson.Get(string(data), "users.#(age>30)#.name|email")

Both libraries offer efficient ways to query JSON data, but gojsonq provides a more SQL-like syntax, while gjson uses a compact path syntax. gjson is generally faster and more lightweight, making it ideal for simple queries and large datasets. gojsonq offers more advanced features and a more intuitive query structure for complex operations.

Pros of jsonparser

• Faster performance, especially for large JSON files
• Lower memory usage due to not parsing the entire JSON structure
• Supports streaming JSON parsing for handling large datasets

Cons of jsonparser

• Less intuitive API, requiring more manual work for complex queries
• Limited functionality compared to gojsonq's rich query features
• No built-in support for aggregations or advanced filtering

Code Comparison

gojsonq example:

result := gojsonq.New().File("data.json").
    From("users").
    Where("age", ">", 30).
    Select("name", "email").
    Get()

jsonparser example:

var users []User
jsonparser.ArrayEach(data, func(value []byte, dataType jsonparser.ValueType, offset int, err error) {
    age, _ := jsonparser.GetInt(value, "age")
    if age > 30 {
        name, _ := jsonparser.GetString(value, "name")
        email, _ := jsonparser.GetString(value, "email")
        users = append(users, User{Name: name, Email: email})
    }
}, "users")

The code comparison demonstrates that gojsonq provides a more declarative and concise approach to querying JSON data, while jsonparser requires more manual implementation but offers finer control over parsing and memory usage. gojsonq is better suited for simple to moderately complex queries, while jsonparser excels in performance-critical scenarios or when dealing with very large JSON files.

Pros of fastjson

• Significantly faster JSON parsing and serialization
• Lower memory usage and fewer allocations
• Supports streaming JSON parsing for large files

Cons of fastjson

• Less feature-rich query capabilities compared to gojsonq
• Steeper learning curve due to low-level API
• Limited built-in data manipulation functions

Code Comparison

gojsonq example:

result := gojsonq.New().File("data.json").From("users").Where("age", ">", 30).Get()

fastjson example:

var p fastjson.Parser
v, err := p.Parse(jsonData)
users := v.GetArray("users")
for _, user := range users {
    if age := user.GetInt("age"); age > 30 {
        // Process user
    }
}

Summary

fastjson excels in performance and efficiency, making it ideal for high-throughput applications or working with large JSON datasets. It offers a low-level API that provides fine-grained control over parsing and manipulation.

gojsonq, on the other hand, provides a more user-friendly interface with powerful query capabilities, making it easier to extract and manipulate JSON data. It's better suited for applications where ease of use and expressive queries are prioritized over raw performance.

Choose fastjson for performance-critical applications or when working with large JSON streams. Opt for gojsonq when you need a simple, expressive way to query and manipulate JSON data in your Go applications.

Pros of easyjson

• Focuses on high-performance JSON encoding/decoding
• Generates code for faster serialization/deserialization
• Supports custom MarshalJSON/UnmarshalJSON methods

Cons of easyjson

• Limited to JSON processing, lacks query capabilities
• Requires code generation step, increasing build complexity
• Less flexible for dynamic JSON manipulation

Code Comparison

easyjson:

//easyjson:json
type Person struct {
    Name string `json:"name"`
    Age  int    `json:"age"`
}

gojsonq:

result := gojsonq.New().File("data.json").
    From("users").
    Where("age", ">", 18).
    Select("name", "age").
    Get()

Key Differences

• Purpose: easyjson focuses on fast JSON processing, while gojsonq provides JSON querying capabilities
• Performance: easyjson offers better performance for JSON encoding/decoding
• Flexibility: gojsonq allows for more dynamic JSON manipulation and querying
• Usage: easyjson requires code generation, gojsonq works with runtime queries
• Scope: easyjson is specific to JSON, gojsonq supports both JSON and YAML

Both libraries serve different purposes within the Go ecosystem. easyjson is ideal for applications requiring high-performance JSON processing, while gojsonq is better suited for projects needing flexible JSON querying and manipulation.

Pros of gabs

• More flexible and dynamic JSON manipulation, allowing for creation and modification of complex structures
• Better performance for large JSON documents due to its underlying data structure
• Supports both encoding and decoding of JSON data

Cons of gabs

• Less intuitive query syntax compared to gojsonq's fluent interface
• Lacks some advanced querying features like conditional filtering and aggregation
• May require more manual handling for certain operations

Code Comparison

gabs:

json, _ := gabs.ParseJSON([]byte(`{"foo":{"bar":"baz"}}`))
value, _ := json.Path("foo.bar").Data().(string)
json.Set(42, "foo", "number")

gojsonq:

value := gojsonq.New().FromString(`{"foo":{"bar":"baz"}}`).
    Find("foo.bar").(string)
result := gojsonq.New().FromString(`{"foo":{"bar":"baz"}}`).
    From("foo").Where("bar", "=", "baz").Get()

Both libraries offer JSON parsing and querying capabilities, but gabs focuses more on dynamic manipulation, while gojsonq provides a more intuitive querying interface. gabs is generally better for complex JSON modifications, while gojsonq excels in data extraction and filtering operations.