Go (Golang) vs. TypeScript (Bun): 2026 Performance Benchmark and Backend Strategy
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In static performance tests, Bun (TypeScript) reaches a peak of 200,000 RPS, matching Go (Fiber). However, in real-world database scenarios, Go outperforms Bun with 84,000 RPS, significantly lower latency, and superior connection pool management. While Bun immediately occupies all 500 database connections, Go dynamically scales them based on load, proving more stable for complex microservices,.
The Evolution of Modern Backend Runtimes
The landscape of backend development is currently defined by a tension between developer velocity and raw performance. For many, the greatest appeal of using JavaScript—and more recently, TypeScript—for both frontend and backend development is the ability to become a “full-stack” developer with a single language. This unified language approach allows teams to create websites and develop APIs seamlessly using the same syntax and ecosystem.
The journey to high-performance TypeScript has been iterative:
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Node.js (2009): The first widely adopted JavaScript runtime that brought serverside applications to the mainstream. -
Deno (2018): Introduced to provide enhanced security and native TypeScript support. -
Bun (2021): Built specifically to boost performance, Bun is written in Zig, a low-level language that allows for precise memory management and high-speed execution,.
On the other side of the spectrum, Go (Golang) was developed specifically for serverside applications and optimized for networking from its inception. This leads to a critical question for 2026: Should developers stick with the TypeScript ecosystem or switch to Go for better performance?
Infrastructure and Benchmark Methodology
To ensure the results are applicable to production environments, the testing was conducted on AWS using a setup identical to client-facing applications.
The Cluster Configuration
The testing environment utilized an EKS (Elastic Kubernetes Service) managed cluster.
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Instances: Two application instances were deployed. -
Resource Limits: Each instance was restricted to a single CPU core limit on large instances to isolate performance metrics. -
Traffic Simulation: 40 independent clients running on different ports were used to generate load. -
Stress Strategy: The number of threads in each client was slowly increased to identify the point of failure for each application.
The Database Environment
For the “Real World” test, the infrastructure was expanded:
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Storage: Two additional EC2 storage-optimized instances were provisioned specifically for PostgreSQL. -
Bottleneck Prevention: Large instances were chosen for the databases to ensure that any performance lag originated from the application code, not the database hardware.
Static Performance Analysis: High-Speed I/O
The first test involved simple HTTP GET requests returning static responses to the client. This test measures the baseline overhead of the runtimes without external dependencies.
| Metric | Go (Fiber) Performance | TypeScript (Bun) Performance |
|---|---|---|
| Peak Throughput | Highly competitive, similar to Bun | 200,000 RPS (on 2 CPU instances) |
| Latency | Very similar to Bun | Very similar to Go |
| CPU Usage | Efficient and stable | Efficient and stable |
| Memory Behavior | Static; does not increase with load | Fluctuates based on load |
In this scenario, Bun demonstrated one of the best results seen to date, reaching 200,000 requests per second. While Bun performed slightly better in raw throughput, the overall performance profile between Go and Bun in static tests was remarkably similar,.
Real-World Test: Database Interaction and Stability
The second test introduced a relational database (PostgreSQL). Each application received a POST request, saved the item to the database, and returned an ID to the client. This test added metrics for database load and connection management.
1. Throughput and Stability
In this more complex scenario, the performance gap widened. Go was clearly more stable and achieved a higher throughput of 84,000 RPS.
2. Latency Comparison
Go performed significantly better than Bun regarding latency in the database test. For real-time applications where every millisecond counts, Go’s ability to handle concurrent database writes with lower latency is a decisive factor.
3. Connection Pool Management (Specific Metrics)
A critical technical difference was observed in how each runtime handles the database connection pool. The limit was set to 250 connections per instance (500 total).
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Bun’s Approach: Bun immediately creates all 500 connections upon startup or load. -
Go’s Approach: Go slowly increases the connection count based on the actual load requirements.
4. Database Instance Load
Go also managed the CPU usage of the Postgres instance more effectively. When interacting with microservices or databases, Go continues to outperform TypeScript runtimes in resource efficiency.
How-To: Reproducing the Benchmark
Following these steps allows you to verify the performance metrics in your own AWS environment.
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Prepare the Codebase: Utilize the source code available in the public GitHub repo (testing Go Fiber and Bun). -
Deploy the EKS Cluster: Set up two instances with a 1-CPU core limit. -
Configure Postgres: Provision two EC2 storage-optimized instances. Use large instance types to ensure the database is not the bottleneck. -
Set Connection Limits: Configure your application to a maximum of 250 connections per instance. -
Execute the Load Test: -
Launch 40 independent clients. -
Slowly increase threads until failure. -
Monitor the heat maps for Latency, Throughput, CPU, and Memory over a 2-hour window.
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FAQ: Addressing Key Technical Concerns
Why does Go’s memory usage look different in the charts?
Interestingly, during the tests, Go’s memory usage did not increase as the load increased, whereas Bun’s memory usage showed more typical fluctuations. This points to Go’s highly optimized garbage collection and memory allocation for network-heavy tasks.
Is Bun written in a specific language to make it faster?
Yes, Bun is written in Zig, which is a low-level language. This choice was intentional to enable precise memory management and the high speeds observed in the static tests where it hit 200,000 RPS,.
Which should I choose for a microservices architecture?
If your microservices interact heavily with databases or other services, Go is the better choice as it remains more stable and provides better latency under those specific “real-world” conditions. However, the performance gap is shrinking.
Does Bun support TypeScript natively?
Yes, one of the improvements Bun (and previously Deno) brought to the ecosystem is native support for TypeScript, eliminating the need for complex transpilation steps required in older environments.
Final Verdict: Expertise and Experience-Driven Insights
The benchmark data leads to a nuanced conclusion for 2026.
TypeScript with Bun has reached a level of maturity where its performance is “decent” and even “top-tier” for static I/O, making it a viable choice for backend applications where developer comfort with the JavaScript ecosystem is a priority,.
However, Go (Golang) remains the superior choice for high-load, real-world use cases. Its ability to maintain 84,000 RPS with stable latency and intelligent connection pooling proves that its optimization for networking is still unmatched. While the gap between TypeScript runtimes and serverside languages like Go is shrinking, Go continues to hold the lead in efficiency and stability when external system interactions are involved,.
For a system that requires predictable scaling and minimal latency under heavy database load, the evidence points toward Go as the more robust solution.
The data presented in this article is derived from a 2-hour compressed benchmark test conducted on AWS production-grade infrastructure, comparing Go Fiber and Bun runtime performance.