xTom - The 18 Best Linux Benchmarking Scripts

When it comes to benchmarking your Linux servers, it's helpful because it:

Validates that you're getting the performance you're paying for
Establishes performance baselines for future comparison
Identifies potential bottlenecks before they impact applications
Provides objective metrics when comparing different hosting options

The only issue is there are quite a few different Linux benchmarking scripts out there nowadays, and it can be rather confusing picking the right one that gives you the data you want.

That said, have no fear: in this guide we'll cover the 18 best Linux benchmarking tools that'll help you measure and analyze various aspects of your server performance, from CPU and memory to storage and network capabilities. Let's dive in.

Quick assessment tools

1. YABS (Yet Another Benchmark Script)

YABS has become the go-to benchmarking script for many system administrators due to its comprehensive approach and simplicity.

What YABS tests:

System information (CPU, cores, frequency, architecture)
Disk performance (sequential and random I/O)
Network performance (global download/upload speeds)
CPU performance (single and multi-core benchmarks)

YABS is ideal for quick assessments of new VPS instances or dedicated servers, providing an excellent first-look at overall system performance.

2. nench.sh

When you need a fast, lightweight benchmark that doesn't require installation, nench.sh provides a good balance of speed and comprehensiveness.

What nench.sh tests:

Basic system information
CPU performance (via OpenSSL)
Memory and storage I/O performance
Network speed testing

nench.sh is perfect for quick comparisons between different providers or instances, especially when evaluating options for a new deployment.

Comprehensive benchmarking suites

3. Phoronix Test Suite

The Phoronix Test Suite is one of the most comprehensive benchmarking platforms available, with over 450 test profiles and 100 test suites.

What Phoronix tests:

System-wide performance profiling
Targeted subsystem testing (CPU, GPU, disk, memory)
Application-specific benchmarks (web servers, databases, etc.)
Cross-platform comparison with global result database

Phoronix is particularly valuable for its extensive test library and ability to compare your results against a global database of systems.

4. UnixBench

As one of the oldest and most comprehensive benchmarking suites, UnixBench provides a holistic view of system performance with a single score that can be compared across different systems.

What UnixBench tests:

System call overhead
Process creation speed
Pipe throughput
Filesystem operations
Shell scripts execution performance

UnixBench is excellent for establishing baseline performance and comparing different generations of hardware or OS configurations.

CPU and memory benchmarks

5. Geekbench

When it comes to CPU and memory performance testing, Geekbench stands out for its comprehensive approach and standardized scoring system.

What Geekbench tests:

Single-core performance
Multi-core performance
Memory performance
Compute benchmarks for various APIs

Geekbench provides standardized scores that are easily comparable across different systems and platforms.

6. stress-ng

Understanding how your system performs under load is critical for capacity planning. stress-ng is designed to stress test various system components to their limits.

What stress-ng tests:

CPU stress testing with various algorithms
Memory testing with different access patterns
I/O stress on storage subsystems
System stability under extreme conditions

stress-ng is invaluable for testing system stability and identifying performance degradation under heavy load conditions.

7. stressapptest

Originally developed by Google, stressapptest focuses on memory and I/O subsystem validation.

What stressapptest tests:

Memory subsystem errors
I/O path stability
System performance under sustained load

stressapptest is particularly valuable for validating new hardware or after component replacements to ensure system stability.

Storage benchmarks

8. Fio (Flexible I/O Tester)

For detailed storage performance analysis, Fio is the industry standard tool, offering granular testing with highly customizable parameters.

What Fio tests:

Sequential read/write speeds
Random read/write performance (IOPS)
Mixed workloads with adjustable read/write ratios
I/O latency and queue depth impact

Fio excels at revealing the true capabilities of modern storage systems, especially when configuring databases or I/O-intensive applications.

9. Bonnie++

A classic tool for filesystem performance testing, Bonnie++ focuses on file operations typical in server workloads.

What Bonnie++ tests:

File creation and deletion
Sequential and random reads and writes
Metadata operations (file seeks)

Bonnie++ is particularly useful for comparing different filesystem types or mount options.

10. IOzone

IOzone offers comprehensive filesystem performance testing with support for various file operations and access patterns.

What IOzone tests:

Read/write operations with different record sizes
Random and sequential access patterns
File operations under various load conditions
Performance across different file sizes

IOzone is valuable for optimizing filesystem settings and identifying performance characteristics across different workloads.

Network benchmarks

11. iperf3

The standard tool for measuring network throughput, jitter, and packet loss between systems.

What iperf3 tests:

Network bandwidth (TCP/UDP)
Jitter and packet loss
Bidirectional performance
Multiple parallel stream capabilities

iperf3 is essential for evaluating network performance between data centers or within infrastructure components.

12. nuttcp

An alternative to iperf3, nuttcp provides additional network testing capabilities.

What nuttcp tests:

TCP and UDP throughput
Network performance with different buffer sizes
Latency and packet loss statistics
Data transfer efficiency

nuttcp is particularly useful for evaluating network performance in more specialized network environments.

13. speedtest-cli

For measuring internet bandwidth to external locations, speedtest-cli provides a command-line interface to Speedtest.net.

What speedtest-cli Tests

Download speeds to global servers
Upload performance
Connection latency
ISP and server information

speedtest-cli is valuable for evaluating external connectivity quality, particularly for services that interact with users over the internet.

Application-specific benchmarks

14. wrk (HTTP Benchmark)

For web servers and API endpoints, wrk provides powerful HTTP benchmarking capabilities.

What wrk Tests

HTTP request throughput (requests per second)
Latency distribution
Error rates under load
Server performance with concurrent connections

wrk is essential for capacity planning and optimizing web applications and APIs.

Database benchmarks

15. Sysbench

Sysbench excels at testing database performance, particularly for MySQL/MariaDB and PostgreSQL.

What Sysbench Tests

OLTP workload simulation
CPU performance
Memory operations
File I/O performance

Sysbench is invaluable for optimizing database configurations and validating performance after changes.

16. pgbench

For PostgreSQL-specific benchmarking, pgbench provides detailed performance insights.

What pgbench Tests

Transaction processing performance
Connection handling efficiency
Query execution times
Scalability with concurrent clients

pgbench is essential for PostgreSQL tuning and configuration optimization.

Specialized tools

17. Intel MLC (Memory Latency Checker)

For systems with Intel processors, MLC provides detailed memory subsystem analysis.

What MLC Tests

Memory bandwidth
Memory latency
NUMA effects
Cache performance

MLC is particularly valuable for optimizing memory-intensive applications and understanding NUMA effects.

18. HPC Challenge Benchmark

For high-performance computing workloads, the HPC Challenge Benchmark provides comprehensive performance evaluation.

What HPC Challenge Tests

HPL (High-Performance Linpack)
STREAM memory bandwidth
PTRANS (parallel matrix transpose)
RandomAccess
FFT (Fast Fourier Transform)

The HPC Challenge is helpful for evaluating systems intended for scientific computing or other high-performance workloads.

Linux benchmarking tools comparison

Tool	Category	Complexity	Installation	Real-world Correlation	Open Source	GUI Available
YABS	All-in-one	Low	None (script)	Medium	Yes	No
nench.sh	All-in-one	Low	None (script)	Medium	Yes	No
Phoronix Test Suite	All-in-one	High	Package	High	Yes	Yes
UnixBench	System	Medium	Build	Medium	Yes	No
Geekbench	CPU/Memory	Low	Binary	High	No	Yes
stress-ng	Stress Test	Medium	Package	Medium	Yes	No
stressapptest	Memory/IO	Medium	Package	Medium	Yes	No
Fio	Storage	High	Package	Very High	Yes	No
Bonnie++	Storage	Medium	Package	High	Yes	No
IOzone	Storage	High	Package	High	Yes	No
iperf3	Network	Medium	Package	Very High	Yes	No
nuttcp	Network	Medium	Package	Very High	Yes	No
speedtest-cli	Internet	Low	Package/pip	Very High	Yes	No
wrk	HTTP	Medium	Build	Very High	Yes	No
Sysbench	Database	High	Package	Very High	Yes	No
pgbench	PostgreSQL	Medium	Package	Very High	Yes	No
Intel MLC	Memory	Medium	Binary	High	No	No
HPC Challenge	HPC	Very High	Build	Very High	Yes	No

How to choose the right Linux benchmarking tool

Different scenarios call for different benchmarking approaches:

Initial server evaluation: YABS or nench.sh for quick assessment
Detailed performance profiling: Phoronix Test Suite for comprehensive analysis
Storage-centric workloads: Fio, Bonnie++, and IOzone for in-depth I/O testing
High-performance computing: Intel MLC, and HPC Challenge for optimizing thread placement and memory access
Network-critical applications: iperf3, nuttcp, and speedtest-cli for detailed network analysis
Web application hosting: wrk for HTTP performance testing
Database servers: Sysbench and pgbench for optimizing database performance

Ultimately, a combination of many of these tools provides the most complete picture of your system's capabilities.

Best practices for meaningful benchmarking

To ensure your benchmarking results are useful:

Create a consistent testing environment: Minimize background processes and external factors
Run multiple test iterations: Single runs can be misleading; average multiple runs
Benchmark with realistic workloads: Test patterns that match your actual application behavior
Document your methodology: Record specific test parameters for future comparisons
Consider performance variability: Especially in virtualized or cloud environments
Test at different times: Performance can vary based on time of day, especially in shared environments
Validate with cross-tool testing: Use multiple tools that test the same subsystem to confirm findings
Account for distribution differences: Package names, versions, and default configurations can vary significantly between Linux distributions
Check for distribution-specific optimizations: Some benchmarking tools may perform differently on various distributions due to compiler flags or kernel parameters

Conclusion

These 18 Linux benchmarking tools provide comprehensive insights into your infrastructure's performance characteristics, helping you optimize deployments, troubleshoot bottlenecks, and make informed decisions.

For reliable infrastructure that consistently delivers on its performance promises, consider solutions like those offered by xTom (hello! that's us ;-), which provides dedicated servers, colocation, IP transit services, and more. Something you can verify with the benchmarking tools covered in this article.

For those who need flexible, scalable virtual servers, V.PS (xTom's VPS brand) offers NVMe-powered KVM VPS instances that deliver exceptional performance.

Whatever your hosting needs, these benchmarking tools will help ensure you're getting the performance you require for your applications and services.

Thanks for reading and have fun benchmarking!

Frequently asked questions about Linux benchmarking

How do synthetic benchmarks compare to application benchmarks?

Synthetic benchmarks measure raw system capabilities, while application benchmarks simulate real-world workloads. Both provide valuable insights—synthetic tests offer standardized comparison points, while application tests better predict actual performance for specific use cases.

How frequently should benchmarking be performed?

Benchmark when deploying new systems, after hardware or significant software changes, and periodically (quarterly is common) to detect performance degradation. Also consider benchmarking during capacity planning exercises.

How can I benchmark applications with specific requirements?

For specialized workloads, custom benchmarks using tools like Phoronix Test Suite's test creation capabilities or application-specific tools (e.g., pgbench for PostgreSQL or mysqlslap for MySQL) often provide more relevant insights than general-purpose benchmarks.

How do I interpret benchmark results in virtualized environments?

Virtualized environments often show more performance variability than bare metal. Look for performance patterns rather than absolute numbers, and consider "noisy neighbor" effects when analyzing unexpected results.

Can benchmarking tools impact production systems?

Intensive benchmarks consume significant resources and can impact production workloads. Always schedule resource-intensive benchmarking during maintenance windows or on staging systems that mirror production configurations.

How do I benchmark distributed systems effectively?

For distributed systems, coordinated multi-node benchmarking using tools like distributed Phoronix instances or specialized tools like Distributed Jmeter provide more meaningful results than single-node tests.

How do benchmarking tools differ across Linux distributions?

While most benchmarking tools function similarly across distributions, there can be notable differences in package availability, default configurations, and even performance due to distribution-specific optimizations. Always check distribution-specific documentation when available, and consider package name differences when installing tools (apt for Debian/Ubuntu, yum for CentOS/RHEL 7, dnf for newer RPM-based systems, pacman for Arch, and zypper for SUSE).

What role does benchmarking play in capacity planning?

Benchmarking helps establish performance baselines and identify scaling limits. By simulating increased load using tools like stress-ng or application-specific load generators, you can predict when infrastructure expansion will be necessary.

Is cloud instance performance consistent?

Cloud instance performance can vary significantly based on the provider, instance type, and even time of day. Running benchmarks at different times and days of the week can help identify performance variability patterns that might affect your applications.