Hello devs, if you've designed distributed systems and software, you may know that System design is about making crucial decisions to balance various trade-offs, which determine a system's functionality, performance, and maintainability.
Understanding these trade-offs when building or scaling a system helps engineers and architects make informed choices that align with business and technical requirements.
Earlier, I have shared many popular system design questions like , and today, we will delve into 15 critical system design trade-offs that every tech professional should know.
Whether you are learning System design or preparing for a System design interview, these tradeoffs will greatly help you articulate your answer and justify your selection and design for the interview.
Though, if you are learning these concepts as part of interview prep then I also suggest you check out sites like , , and
15 System Design Tradeoffs for Experienced Developers and Software Architects
Without any further ado, here is a list of 15 system design tradeoffs that I think play an important role in designing real-world systems. Knowing these will help you to better architect a system that can withstand the test of time in production.
1. Horizontal vs Vertical Scaling
Vertical scaling, or scaling up, involves enhancing the power of existing servers by adding more CPU, RAM, or storage.
It is simple but has a limit. Horizontal scaling, or scaling out, means adding more servers to distribute the load.
While this approach can theoretically handle unlimited growth, it requires careful management of distributed systems and can introduce complexities such as data consistency and load balancing.
3. Latency vs. Throughput
Latency is the time taken to process a single task, while throughput is the total number of tasks processed in a given time frame.
Optimizing for latency means prioritizing quick responses, suitable for systems like online gaming or high-frequency trading.
Conversely, optimizing for throughput is ideal for batch processing systems, where the goal is to maximize the volume of processed data over time.
5. Consistency vs. Availability (CAP Theorem)
This is another important System design concept and tradeoff a senior engineer should remember.
According to the CAP theorem, a distributed system can only guarantee two out of three properties: Consistency, Availability, and Partition Tolerance.
Consistency ensures that all nodes see the same data at the same time, while availability means the system is always operational.
Choosing consistency over availability is crucial for financial transactions, while for social media feeds, availability may take precedence.
7. Read-Through vs. Write-Through Caching
In a read-through cache, data is loaded into the cache on a read miss. This approach reduces cache pollution but might increase latency for uncached data.
In a write-through cache, data is simultaneously written to the cache and the database, ensuring consistency but at the cost of write performance.
9. Batch vs. Stream Processing
Batch processing handles data in chunks, ideal for tasks like payroll processing, where the entire dataset is processed at once.
Stream processing deals with continuous data flow, suitable for real-time analytics, where immediate data processing is crucial.
11. Long Polling vs. WebSockets
Long polling allows a client to wait for data from the server, which is resource-intensive and can cause delays.
WebSockets offer a persistent two-way connection, enabling real-time data transfer.
This is ideal for applications like chat systems or live dashboards, where continuous updates are necessary.
Another benefit of WebSockets it that they run on port 80 which is also used by HTTP and hence almost always open. You don't need to open another port on firewall which means less headache as you don't have to deal with network teams .
13. Monolithic vs. Microservices Architecture
This tradeoff is probably the most important one for system design interviews.
Monolithic architecture involves a single, unified codebase, simplifying development and deployment but making scaling and maintenance challenging.
Microservices break down the system into independent services, enabling scalability and flexibility at the cost of increased operational complexity.
15. REST vs. GraphQL
REST uses standard HTTP methods and endpoints, which are simple and scalable but can lead to over-fetching or under-fetching of data.
GraphQL, on the other hand, allows clients to query exactly what they need, reducing the amount of data transferred and improving performance, especially for complex or nested data requirements.
, and practice websites which you can check to better prepare for System design interviews. Most of these courses also answer questions I have shared here.
: This is another great platform to practice System design problems for interviews. It has more than 120+ System design problems, many of which are free and it also has a proper structure to solve them.
: A specialized site for interview prep especially for FAANG companies like Amazon and Google, They also have a great system design course and many other materials that can help you crack FAAN interviews
by Martin Kleppmann: A comprehensive guide that covers the principles and practices for designing scalable and reliable systems.
on GitHub: A curated list of resources, including articles, books, and videos, to help you prepare for system design interviews.
: Check out channels like "Gaurav Sen" and "Tech Dummies" for insightful videos on system design concepts and interview preparation.
image_credit --- ByteByteGo
You should also remember to combine theoretical knowledge with practical application by working on real-world projects and participating in mock interviews. Continuous practice and learning will give you confidence for system design interviews.
That's all about 15 essential System Design tradeoffs that every developer needs to be aware of. Understanding these system design trade-offs is crucial for architects and developers as they enable the design of robust, scalable, and maintainable systems.
By weighing the pros and cons of each approach, one can make informed decisions that align with the technical and business requirements.
Whether you're optimizing for performance, scalability, or consistency, recognizing these trade-offs will help you build better systems that meet user expectations and handle future growth.
All the best with your interviews !!
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