Latency vs. Throughput: Understanding the Key Differences

When optimizing system performance, two critical metrics often come into play: latency and throughput. While they are related, they measure different aspects of performance. Understanding their differences is crucial for designing efficient systems, whether in networking, databases, or computing.

What is Latency?

Latency refers to the time it takes for a single unit of data (e.g., a packet, request, or transaction) to travel from its source to its destination. It is typically measured in milliseconds (ms).

Examples of Latency:

Network Latency: Time for a data packet to travel from a client to a server.
Disk Latency: Time taken to read/write data from a storage device.
Database Latency: Time for a query to execute and return results.

What is Throughput?

Throughput refers to the amount of data processed or transferred over a given period. It is usually measured in bits per second (bps), requests per second (RPS), or transactions per second (TPS).

Examples of Throughput:

Network Throughput: Amount of data (e.g., Mbps) transferred over a network in a second.
Database Throughput: Number of queries processed per second.
API Throughput: Requests handled per second by a web server.

Key Differences Between Latency and Throughput

Factor	Latency	Throughput
Definition	Time delay for one operation	Amount of data processed over time
Measurement	Milliseconds (ms)	Bits per second (bps), RPS, TPS
Focus	Speed of a single transaction	Volume of transactions
Impact	User experience (responsiveness)	System capacity (scalability)

Latency vs. Throughput: The Pipeline Analogy

Imagine a water pipeline:

Latency = Time for a single drop to travel from start to end.
Throughput = Total amount of water flowing per second.

How Latency and Throughput Affect Performance

High Latency + High Throughput: A system may handle many requests (high throughput) but with slow responses (high latency).
Low Latency + Low Throughput: Fast responses (low latency) but limited capacity (low throughput).

Optimization Goal:

Reduce Latency → Faster responses (e.g., caching, CDNs).
Increase Throughput → Handle more requests (e.g., load balancing, parallel processing).

Conclusion

Latency measures delay (speed of one operation).
Throughput measures capacity (volume of operations per second).
Balancing both is key for optimal system performance.

Latency vs. Throughput