What’s the Real Difference Between QPS and TPS? A Deep Dive into System Throughput

QPS

QPS (Queries Per Second) measures how many queries a server can handle each second, reflecting the maximum throughput of a specific query server.

TPS

TPS (Transactions Per Second) counts the number of transactions processed per second; a transaction spans from the client request to the server’s response.

Difference Between QPS and TPS

TPS counts complete transactions, including user request, internal server processing, and server response. QPS counts every individual request to the server, which may be multiple per transaction.

For example, a page visit may generate one transaction (TPS) but three server requests (QPS). Similarly, a fast eater can finish 10 buns per second (TPS) while a slower eater handles only 1 bun per second (QPS); both are different rates.

Concurrency

Concurrency (or concurrency level) indicates the number of requests a system can handle simultaneously, reflecting load capacity.

Throughput

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

Key Parameters

QPS/TPS: number of requests or transactions per second.

Concurrency: number of simultaneous requests/transactions.

Response Time: typically the average response time.

Relationship: QPS (or TPS) = Concurrency / Average Response Time.

When either QPS or concurrency reaches its limit, overall throughput stops increasing and may even decline due to overload, context switching, and resource contention.

PV (Page View)

PV counts each page load or refresh as a view, measurable from daily access logs.

UV (Unique Visitor)

UV counts distinct users visiting a site within a day, derived by deduplicating logs.

DAU (Daily Active Users)

DAU measures the number of unique users who interact with a product in a single day.

MAU (Monthly Active Users)

MAU counts distinct users active over a month.

System Throughput Evaluation

Designing a system requires considering CPU usage, I/O, external service latency, and estimating performance limits.

Beyond QPS and concurrency, daily PV is another dimension for capacity planning.

By analyzing access logs, one can infer daily traffic patterns and estimate maximum daily throughput.

Typical Technical Approaches

1. Identify the system’s peak TPS and daily PV, which usually have a stable relationship (excluding holidays or seasonal effects).

2. Use stress testing or experience to determine peak TPS, then calculate the maximum daily throughput based on the TPS‑PV relationship.

Fundamental Concepts and Formulas for Software Performance Testing

Performance testing focuses on response time, resource utilization, scalability, maximum concurrent users, potential bottlenecks, hardware upgrades, and 24/7 availability.

From a developer’s perspective, considerations include architecture design, database design, code efficiency, memory usage, thread synchronization, and resource contention.