Comprehensive Performance Comparison of PHP, Go, and Node.js Frameworks
Data Source
The data for this performance comparison is sourced from https://www.techempower.com/benchmarks/#section=data-r18&hw=cl&test=query. This website provides rich and authoritative performance test data for different programming languages and frameworks, providing strong support for our analysis.
Analyzed Metrics
- JSON Serialization Serialized Response: Mainly measures the performance of the framework when serializing data into JSON format and returning the response. This process does not involve specific database operations, focusing on the framework's own data processing and output capabilities.
- Plaintext Simple Response: Tests the speed at which the framework returns a simple text response. Similarly, it does not involve database interaction and is used to evaluate the performance of the framework in the most basic HTTP response scenario. This scenario is common in the HTTP OPTIONS method. In function computing, the gateway can also respond to this request to save operating expenses.
- Single Query Single - line Query: Examines the performance of the framework in executing a single - line database query operation and returning the result. This involves the interaction efficiency between the framework and the database and the processing speed of the query result.
- Multiple Queries Multiple - line Query: Evaluates the performance of the framework when executing multiple database query operations. Compared with single - line queries, it can better test the framework's processing ability and resource management ability in complex data query scenarios.
- Data Updates Data Update: Analyzes the performance of the framework during data update operations, including aspects such as interaction with the database, data validation, and the execution efficiency of the update logic.
Analyzed Objects
Considered Solutions
- Node.js (Function Computing): Leveraging Node.js's event - driven and non - blocking I/O model, it has unique advantages in function computing scenarios. It can efficiently handle a large number of concurrent requests and shares common syntax with front - end development, facilitating front - end and back - end collaborative development.
- Go (Single - machine Deployment): The Go language is known for its high - performance concurrency and lightweight runtime environment. The single - machine deployment here does not only refer to one machine but is different from the "gateway + function computing" deployment method, giving full play to the performance advantages of the Go language in an independent server environment.
Specific Applications
- echo (Go): A lightweight web framework in the Go language, it is simple to use, has high performance, and has good community support. In this performance comparison, it is analyzed as a typical application framework of the Go language.
- go - pgx - easyjson: This is a combination of pgx (a PostgreSQL driver library for the Go language) and easyjson (a library for efficient JSON serialization and deserialization), aiming to give full play to the performance advantages of the Go language in handling PostgreSQL databases and JSON data.
- nodejs - postgres (ORM): An application based on Node.js that uses ORM (Object - Relational Mapping) technology to operate the PostgreSQL database. ORM technology can simplify database operations and improve development efficiency but may have a certain impact on performance.
- php (nginx): As a widely used server - side scripting language, PHP is often used in conjunction with the nginx server. Nginx, as a high - performance HTTP and reverse - proxy server, can work in coordination with PHP to efficiently complete network tasks.
- php - pgsql - raw (nginx): This is a way to directly operate the PostgreSQL database using PHP's native pgsql extension in the nginx server environment. Compared with using frameworks such as ORM, this native operation method may have higher performance in some scenarios.
- lumen (nginx, ORM, MySQL): Lumen is a lightweight PHP framework based on Laravel, combined with the nginx server, ORM technology, and the MySQL database. While providing convenient development functions, its performance compared with other frameworks also needs to be considered.
In this analysis, the PHP + PostgreSQL combination was not seen, and most combinations with Golang were with PostgreSQL, which reflects some preferences and characteristics of different languages in database selection and application scenarios.
Analysis Overview
- Rust vs. C, C++: The Rust language performs extremely well in terms of performance, even exceeding the traditional high - performance languages C and C++. This benefits from Rust's memory - safety mechanism, efficient compilation optimization, and full utilization of underlying hardware resources.
- Java Performance and Popularity: The Java language also shows relatively fast performance, but it is currently unclear about the popularity of these Java frameworks in actual applications. Java is widely used in many large - scale projects due to its rich class libraries, strong enterprise - level development support, and good cross - platform nature, but the popularity of frameworks may vary in different fields and scenarios.
- PHP Performance Analysis: The overall performance of native PHP is not slow, but when used in combination with frameworks, the performance drops significantly. This is mainly because some frameworks, while providing convenient development functions, introduce more intermediate layers and abstract concepts, increasing the complexity and operating overhead of the system.
- Go vs. Node.js Performance Comparison: In terms of data request processing performance, Go is faster than Node.js. Although the test shows that the performance of Go is more than 3 times that of Node.js, part of the performance loss comes from the use of ORM. The performance of writing native Go code is basically the same as using the echo framework, indicating that the echo framework has well maintained the high - performance characteristics of the Go language in its design.
Analysis Details
JSON Serialization Serialized Response
Framework | Performance |
---|---|
echo | 32.8% |
go | 31.9% |
go - pgx - easyjson | 31.4% |
nodejs | 23.6% |
php | 12.5% |
lumen | 1.1% |
In terms of JSON serialization response performance, the Go - language - related frameworks and applications perform well. echo, go, and go - pgx - easyjson rank at the top of the performance list, which benefits from the Go language's efficient JSON processing libraries and optimized memory management mechanisms. The performance of Node.js is at a medium level, while the performance of PHP and lumen is relatively low, reflecting that there is still room for improvement in their JSON serialization processing efficiency.
Plaintext Simple Response
Framework | Performance |
---|---|
fasthttp | 65.3% |
nodejs | 7.9% |
go | 6.4% |
echo | 5.2% |
lumen | 0.1% |
In the simple text response test, fasthttp stands out with extremely high performance. Surprisingly, Go is slower than Node.js in this section. However, when Go switches to the fasthttp third - party library, its performance soars. This shows that the Go language itself has strong performance potential, and by reasonably choosing and using third - party libraries, its performance in specific scenarios can be significantly improved. The performance of lumen in this test is extremely low and needs further optimization.
Single Query Single - line Query
Framework | Performance |
---|---|
echo | 46.2% |
go - pgx - easyjson | 43.1% |
nodejs - postgres | 13.8% |
php - pgsql - raw | 13.8% |
lumen | 1.5% |
In the single - line query performance test, echo and go - pgx - easyjson once again show good performance, with high efficiency in interacting with the database and returning single - line query results. The performance of nodejs - postgres and php - pgsql - raw is comparable and at a medium level, while the performance of lumen is relatively poor, possibly due to the complexity of its framework and the use of ORM, which leads to a decline in query performance.
Multiple Queries Multiple - line Query
Framework | Performance |
---|---|
go - pgx - easyjson | 47.8% |
echo | 44.3% |
php - pgsql - raw | 30.0% |
nodejs - postgres | 14.4% |
lumen | 8.1% |
In the multiple - line query scenario, go - pgx - easyjson and echo still perform well and can efficiently handle multiple database query operations. The performance of php - pgsql - raw is also considerable, exceeding that of nodejs - postgres. Although the performance of lumen has improved, there is still a large gap compared with other excellent - performing frameworks.
Data Updates Data Update
Framework | Performance |
---|---|
go - pgx - easyjson | 35.4% |
echo | 31.8% |
php - pgsql - raw | 20.4% |
nodejs - postgres | 8.2% |
lumen | 6.9% |
In the data update performance test, go - pgx - easyjson and echo perform leadingly and can quickly complete data update operations. The performance of php - pgsql - raw is at a medium level, while the data update performance of nodejs - postgres and lumen is relatively low, which may be related to their database operation methods and framework implementation mechanisms.
Summary
- Single - machine Deployment Solution Selection: If the single - machine deployment method is adopted, using echo as the basic framework is a good choice. echo has good community support, and developers can easily obtain various resources and assistance. At the same time, its simple and easy - to - use characteristics can also reduce development costs and the learning curve, and it performs well in terms of performance, meeting the needs of most single - machine deployment scenarios.
- echo vs. fasthttp Selection: If the echo framework has been decided to be used, it is not recommended to consider fasthttp anymore. Although echo supported fasthttp in version 2, the author of echo explained the reasons for giving up in https://github.com/labstack/echo/issues/665, mainly to maintain the simplicity of the framework and community compatibility, and to use the standard library as much as possible. This enables echo to better integrate with the community ecosystem while maintaining high performance.
- Function Computing Solution Selection: For function computing scenarios, Node.js is a good choice. It has acceptable performance, can meet the requirements for concurrent processing and response speed in function computing. At the same time, the common syntax of Node.js and the front - end enables front - end and back - end developers to collaborate more easily, reducing communication costs and development difficulties caused by differences in technology stacks.
- PHP Performance and Application Analysis: Judging from the above performance tests, the performance of PHP itself is not a big problem, but its standard library is too old. In actual development, frameworks must be used to improve development efficiency. However, the use of ordinary frameworks will lead to a sharp decline in performance. And due to historical reasons, PHP needs to be combined with Nginx to efficiently complete network tasks, which makes the single - machine deployment steps relatively more, increasing the complexity of deployment and maintenance. When choosing to use PHP for development, multiple factors such as performance, development efficiency, and deployment costs need to be comprehensively considered, and a reasonable decision should be made according to specific application scenarios and requirements.
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