Mastering QPS, TPS, PV, UV, DAU, MAU & System Throughput Explained

This article provides a comprehensive explanation of common performance metrics and concepts used in system design and capacity planning.

1. QPS

QPS ( Queries Per Second) measures the number of queries a server can handle per second, representing the maximum throughput of a specific query service.

2. TPS

TPS ( Transactions Per Second) counts the number of complete transactions per second, where a transaction includes a client request, server processing, and response.

3. Difference between QPS and TPS

TPS reflects the number of complete request‑response cycles per second, while QPS counts every individual query to the server, which may be multiple per transaction.

1) TPS includes:

User requests the server

Server internal processing

Server response to the user

2) QPS is similar but counts each query generated by a page request, which can be multiple.

Example: a single page load may generate three server queries, resulting in one TPS but three QPS.

4. Concurrency

Concurrency (or concurrent degree) indicates how many requests a system can handle simultaneously, reflecting its load capacity.

5. Throughput

Throughput is the number of requests processed by the system per unit time; both QPS and TPS are common quantitative indicators of throughput.

6. PV

PV (Page View) counts each page access or refresh, representing total page visits.

7. UV

UV (Unique Visitor) counts distinct users visiting a site within a day, typically deduplicated by a unique identifier.

8. DAU

DAU (Daily Active Users) measures the number of unique users who interact with a product in a single day, similar to UV but focused on activity.

9. MAU

MAU (Monthly Active Users) counts distinct users who engage with a product over a month.

10. System Throughput Evaluation

When designing a system, consider CPU, I/O, and external service latency to estimate performance. Besides QPS and concurrency, daily PV is another dimension for capacity estimation.

11. Basic Concepts and Formulas for Software Performance Testing

From a user perspective, response time—time from initiating an action to receiving the result—directly impacts perceived performance. From an administrator perspective, key metrics include response time, resource utilization, scalability, maximum supported users, bottleneck identification, and 24/7 availability.

From a developer perspective, evaluate architecture rationality, database design, code efficiency, memory usage, thread synchronization, and resource contention.