Golang vs Python: Why more companies are switching to Go

In the world of software engineering, choosing between Golang and Python often dictates your project's future performance and scalability. While Python remains the undisputed leader in data science and rapid prototyping, Golang (Go) has emerged as the gold standard for cloud-native infrastructure and high-concurrency systems.

At BHSOFT, our development teams leverage the unique strengths of both languages—utilizing Python’s vast ecosystem for AI integration and Go’s lightning-fast execution for enterprise backends. In this expert comparison, we break down the critical trade-offs in speed, syntax, and libraries to help you select the optimal tech stack for your next business-critical application.

Overview of Python and Golang

Below is a clear, expert-level overview to help you understand Python and Golang core strengths.

Python – Fast Development and Multi-Purpose Flexibility

Python is one of the easiest programming languages to learn, with clear syntax that supports rapid prototyping, MVP development, and iterative testing—making it a strong choice for startups and agile teams.

Its extensive library ecosystem powers key domains such as AI, machine learning, data analysis, automation, and web development. Frameworks like TensorFlow, PyTorch, Django, and Flask enable faster development with less code.

Python also benefits from a large global developer pool, allowing companies to hire quickly, scale teams efficiently, and maintain long-term flexibility.

Common long-tail use cases:

Python for rapid application development, Python for AI and machine learning, Python backend development for startups

Pros

• Multi-purpose language with a massive ecosystem
• Fast development and large community support
• Easy learning curve and strong hiring availability

Cons

• Slower in performance-critical applications
• Scaling and hosting costs can be higher than Go

Golang – High Performance and Powerful Concurrency

Golang (Go) is designed for high performance, simplicity, and scalability. As a compiled language, it offers fast execution and efficient resource usage, making it ideal for systems with high traffic and low-latency requirements.

Its built-in concurrency model using goroutines and channels allows developers to handle parallel workloads cleanly and reliably, without complex multithreading logic.

Golang is widely used for backend development, microservices, distributed systems, and cloud-native applications, and powers many modern infrastructure and DevOps tools.

Common long-tail use cases:

Golang for high-performance backend systems, Golang microservices architecture, Golang for cloud-native applications

Pros

• High performance with strong concurrency support
• Lightweight binary deployment
• Easy to maintain at large scale

Cons

• Smaller ecosystem compared to Python
• Fewer available developers, harder to hire

Read more:   Why Django is the Best Python Web Framework

Detailed Comparison: Golang vs Python

1. Performance

Golang is faster because it compiles directly into native binaries, delivering high execution speed and efficient resource usage.

Python runs through an interpreter, which makes it slower in performance-critical scenarios.

For large-scale systems with high concurrency, Go is generally the better choice.

2. Syntax and Developer Experience

Python has a simple and readable syntax, ideal for quick prototyping and MVP development.

Go enforces a clear, consistent code style, which improves maintainability in large codebases.

Python works well for fast MVPs, while Go is better suited for long-term, scalable products.

3. Ecosystem and Libraries

Python offers a rich ecosystem covering AI/ML, web development, automation, and data processing.

Golang focuses mainly on backend, server-side, and cloud-native development, with fewer libraries than Python but strong core tooling.

4. Popularity and Job Opportunities

Python has been around longer, resulting in more projects and job postings worldwide.

Golang is growing rapidly in backend, cloud, and microservices roles.

For beginners, Python is easier to enter the job market, while Go is often seen as a high-value specialized skill.

Read more: The Best Web Development Tools to Use

Infrastructure and System Costs

Golang typically uses less CPU and RAM, resulting in lower long-term hosting costs at scale.

Python can consume more resources when scaling, but this overhead is often small compared to development costs.

Talent Acquisition & Development Costs

Navigating the hiring market for these two languages requires a strategic approach to budget and project timelines.

Python: High Accessibility & Competitive Rates With its massive global footprint, the Python developer market is highly liquid. Finding talent is relatively easy, which keeps hiring costs stable.

Average Rates: Typically range from $40–$70/hour, depending on seniority and the complexity of the AI/Data Science requirements.

Golang: Specialized Expertise & Premium Value Go developers are more specialized, often focusing on cloud-native infrastructure and high-concurrency backends. Because the supply of experienced Gophers is lower, they often command a premium.

Average Rates: Generally start at $50–$90+/hour, reflecting their niche expertise in distributed systems and backend performance optimization.

Hiring Costs by Region

Rates vary by experience level and role.

Key takeaway: Golang developers may command slightly higher rates than Python at the same seniority level due to a smaller talent pool and more specialized backend skills.

Hiring Costs in Vietnam

Senior and mid-level backend developers (Python or Golang) typically earn approximately $1,400–$3,200 per month, depending on experience and tech stack.

Golang developers often receive slightly higher compensation than average backend roles due to talent scarcity.

Why More Companies Are Switching to Go

More companies are switching to Go (Golang) because it strikes a rare balance between high performance, scalability, and development efficiency. As systems grow more complex, especially with microservices and cloud-native architectures, Go’s lightweight concurrency model (goroutines) allows teams to handle thousands of parallel tasks with minimal overhead.

Another key driver is cost efficiency at scale. Go applications are compiled into single binaries, making deployment simpler and reducing infrastructure and maintenance costs. Compared to interpreted languages, Go typically consumes less CPU and memory under heavy load—an advantage for high-traffic systems.

From a business perspective, Go also improves long-term maintainability. Its strict typing, opinionated tooling, and clear coding conventions make large codebases easier to manage across growing teams. While Go developers may cost slightly more to hire, many companies find that faster performance, easier scaling, and fewer production issues offset the higher hiring cost over time.

Conclusion

Choosing between Golang and Python ultimately depends on your project goals, scale, and long-term technical strategy. Python excels in rapid development, flexibility, and a rich ecosystem, making it ideal for MVPs, data-driven applications, and fast iteration. Golang, on the other hand, stands out for its high performance, efficient concurrency, and lower operational costs at scale, which is why many companies are adopting Go for backend systems, microservices, and cloud-native applications.

If you’re unsure which technology best fits your business needs, BHSOFT provides end-to-end software development services using both Golang and Python. From technology consulting and system architecture to backend development and scaling, BHSOFT helps companies build reliable, cost-effective solutions tailored to their growth goals.