Caching Strategies in System Design: Types, Patterns, Trade-offs & Best Practices

Disclosure: This post includes affiliate links; I may receive compensation if you purchase products or services from the different links provided in this article.

System Design Basics - Caching
image_credit - DesignGuru.io

Hello friends, Caching is not just an important topic for System design interviews, its also technique in software development, enabling faster data retrieval, reducing load times, and enhancing user experience.

For developers, mastering caching concepts is crucial as it can significantly optimize application performance and scalability.

In the past, I have talked about common system design questions like API Gateway vs Load Balancer and Horizontal vs Vertical Scaling, Forward proxy vs reverse proxy as well common System Design problems and in this article we will explore the fundamentals of caching in system design and learn different caching strategies that are essential knowledge for technical interviews.

It's also one of the essential System design topics for interview and you must prepare it well.

In this article, you will learn ten essential caching concepts, ranging from client-side and server-side strategies to more advanced techniques like distributed caching and cache replacement policies

So what are we waiting for? let's start

By the way, if you are preparing for System design interviews and want to learn System Design in depth then you can also checkout sites like ByteByteGo, Design Guru, Exponent, Educative, Codemia.io and Udemy which have many great System design courses and a System design interview template like this which you can use to answer any System Design question.

how to answer system design question

If you need more choices, you can also see this list of best System Deisgn courses, books, and websites

P.S. Keep reading until the end. I have a free bonus for you.

What is Caching? Which data to Cache? Where to Cache?

While designing distributed system, caching should be strategically placed to optimize performance, reduce latency, and minimize load on backend services.

Caching can be implemented at multiple layers like

  1. Client-Side Cache
    This involves storing frequently accessed data on the client device, reducing the need for repeated requests to the server. It is effective for data that doesn't change frequently and can significantly improve user experience by reducing latency.

  2. Edge Cache (Content Delivery Network - CDN)
    CDNs cache content at the edge nodes closest to the end-users, which helps in delivering static content like images, videos, and stylesheets faster by serving them from geographically distributed servers.

  3. Application-Level Cache
    This includes in-memory caches such as Redis or Memcached within the application layer. These caches store results of expensive database queries, session data, and other frequently accessed data to reduce the load on the database and improve application response times.

  4. Database Cache
    Techniques such as query caching in the database layer store the results of frequent queries. This reduces the number of read operations on the database and speeds up data retrieval.

  5. Distributed Cache
    In a distributed system, a distributed cache spans multiple nodes to provide high availability and scalability. It ensures that the cached data is consistent across the distributed environment and can handle the high throughput required by large-scale systems.

When designing a caching strategy, it's crucial to determine what data to cache by analyzing usage patterns, data volatility, and access frequency.

Implementing an appropriate cache eviction policy (such as LRU - Least Recently Used, or TTL - Time to Live) ensures that stale data is purged, maintaining the cache's relevance.

Moreover, considering consistency models and cache invalidation strategies is vital to ensure that cached data remains accurate and up-to-date across the system.

And, here is a nice diagram on caching from DesignGuru.io to illustrate what I just said.

System Design Caching cheat shet

10 Caching Basics for System Design Interview

Here are 10 essential caching related basics and concepts every programmer must know before going for any System design interview.

1) client-side caching

Client-side caching is a fundamental technique where data is stored on the user's device to minimize server requests and improve load times. Two primary methods include:

  • Browser Cache: Stores resources like CSS, JavaScript, and images locally to reduce page load times on subsequent visits.
  • Service Workers: Enable offline access by caching responses, allowing applications to function without an internet connection.

In short:

  • browser cache: stores CSS, js, images to reduce load time\
    • service workers: enable offline access by caching response

Here is how client side caching looks like:

client side caching

2) server-side caching

This is another type of caching which involves storing data on the server to expedite response times for user requests.

Key strategies include:

  • Page Caching: Saves entire web pages, allowing faster delivery on subsequent requests .

  • Fragment Caching:
    Caches specific parts of a page, such as sidebars or navigation bars, to enhance loading efficiency.

  • Object Caching:
    Stores expensive query results to prevent repeated calculations

In short:

  • page caching: cache the entire web page
    • fragment caching: cache page components like sidebars, navigation bar\
    • object caching: cache expensive query results

Here is how server side caching looks like:

server side caching

image_credit --- ByteByteGo

3) Database caching

Database caching is crucial for reducing database load and improving query performance. Important techniques include:

  • Query Caching:
    Stores the results of database queries to quickly serve repeat requests.

  • Row Level Caching:
    Caches frequently accessed rows to avoid repeated database fetches.

In short:

  • query caching: cache db query results to reduce load
    • row level caching: cache popular rows to avoid repeated fetches

Here is an example of database caching on AWS:

database caching

4) application-level caching

Application-level caching focuses on caching within the application to reduce computation and data retrieval times. Strategies include:

  • Data Caching: Stores specific data points or entire datasets for quick access.
  • Computational Caching: Caches the results of expensive computations to avoid repeated processing.

In short:

  • data caching: cache specific data points or entire datasets\
    • computational caching: cache expensive computation results to avoid recalculation

application-level caching

5) Distributed caching

Distributed caching enhances scalability by spreading cache data across multiple servers, allowing high availability and fault tolerance.

In short, this type of caching just spreads cache across many servers for scalability

Here is how a distributed cache with Redis looks like:

distributed cache with Redis

6) CDN

Content Delivery Networks (CDNs) are used to cache static files close to users via edge servers, significantly reducing latency and speeding up content delivery.

In short, CDN store static files near users using edge servers for low latency

Also, here is a nice diagram on how CDN Works by DeisgnGuru.io

how CDN Works

7) cache replacement policies

Cache replacement policies determine how caches handle data eviction. Common policies include:

  • Least Recently Used (LRU): Evicts the least recently accessed items first.
  • Most Recently Used (MRU): Evicts the most recently accessed items first.
  • Least Frequently Used (LFU): Evicts items that are accessed least often.

In short:

- LRU: removes the least recently accessed items first\
- MRU: removes the most recently accessed items first\
- LFU: removes items that are accessed least often

cache replacement policies

8) hierarchical caching

Hierarchical caching involves multiple cache levels (e.g., L1, L2) to balance speed and storage capacity. This model is quit popular on CPU.

In short:

  • caching at many levels (L1, L2 caches) for speed and capacity

L1 and L2 Cache

9) cache invalidation

Cache invalidation ensures that stale data is removed from the cache. Methods include:

  • Time-to-Live (TTL): Sets an expiry time for cached data.
  • Event-based Invalidation: Triggers invalidation based on specific events or conditions.
  • Manual Invalidation: Allows developers to manually update the cache using tools.

In short:

- TTL: set expiry time\
- event based: invalidate based on events or conditions\
- manual: update cache using tools

Here is a nice System design cheat sheet about cache invalidation methods by DesignGuru.io to understand this concept better:

cache invalidation strategies

10) caching patterns

Finally, caching patterns are strategies for synchronizing cache with the database. Common patterns include:

  • Write-through: Writes data to both the cache and the database simultaneously.
  • Write-behind: Writes data to the cache immediately and to the database asynchronously.
  • Write-around: Directly writes data to the database, bypassing the cache to avoid cache misses on subsequent reads.

In short:

- write-through: data is written to the cache and the database at once\
- write-behind: data is written to the cache and asynchronously to database\
- write-around: data is written directly to the database, bypassing the cache

Here is another great diagram to understand various caching strategies, courtesy DesignGuru.io, one of the best place to learn System Design.

caching patterns

Best System Design Interviews Resources

And, here are curated list of best system design books, online courses, 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.

  1. DesignGuru's Grokking System Design Course: An interactive learning platform with hands-on exercises and real-world scenarios to strengthen your system design skills.

  2. Codemia.io : This is another great platform to practice System design problems for interviews. It got more than 120+ System design problems, many of them are free and also a proper structure to solve them.

  3. "System Design Interview" by Alex Xu: This book provides an in-depth exploration of system design concepts, strategies, and interview preparation tips.

  4. "Designing Data-Intensive Applications" by Martin Kleppmann: A comprehensive guide that covers the principles and practices for designing scalable and reliable systems.

  5. LeetCode System Design Tag: LeetCode is a popular platform for technical interview preparation. The System Design tag on LeetCode includes a variety of questions to practice.

  6. "System Design Primer" on GitHub: A curated list of resources, including articles, books, and videos, to help you prepare for system design interviews.

  7. Educative's System Design Course: An interactive learning platform with hands-on exercises and real-world scenarios to strengthen your system design skills.

  8. High Scalability Blog: A blog that features articles and case studies on the architecture of high-traffic websites and scalable systems.

  9. YouTube Channels: Check out channels like "Gaurav Sen" and "Tech Dummies" for insightful videos on system design concepts and interview preparation.

  10. ByteByteGo: A live book and course by Alex Xu for System design interview preparation. It contains all the content of System Design Interview book volume 1 and 2 and will be updated with volume 3 which is coming soon.

  11. Exponent: 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 material which can help you crack FAAN interviews.

how to prepare for system design

image_credit - ByteByteGo

Conclusion

That's all about 10 essential Cache related concepts for System design interview. Caching can improve the performance and scalability of your application. So use it carefully. Understanding and implementing these caching concepts can significantly enhance application performance, scalability, and user satisfaction.

Other System Design Articles and Resources you may like

Thanks for reading this article so far. If you like this Twitter system design interview solution then please share it with your friends and colleagues. If you have any questions feel free to ask in the comments.

Bonus\
As promised, here is the bonus for you, a free book. I just found a new free book to learn Distributed System Design, you can also read it here on Microsoft --- https://info.microsoft.com/rs/157-GQE-382/images/EN-CNTNT-eBook-DesigningDistributedSystems.pdf

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Top 10 Caching Strategies for System Design

Disclosure: This post includes affiliate links; I may receive compensation if you purchase products or services from the different links provided in this article.

top 5 caching strategies for System design interviews

image_credit - ByteByteGo

Hello friends, In System design, efficiency and speed are paramount and in order to enhance performance and reduce response times, caching plays an important role. If you don't know what is caching? let me give you a brief overview first

Caching is a technique that involves storing copies of frequently accessed data in a location that allows for quicker retrieval.

For example, you can cache the most visited page of your website inside a CDN (Content Delivery Network) or similarly a trading engine can cache symbol table while processing orders.

In the past, I have shared several system design interview articles like API Gateway vs load balancer, Forward Proxy vs Reverse Proxy as well common System Design problem and in this article we will explore the fundamentals of caching in system design and delves into different caching strategies that are essential knowledge for technical interviews.

It's also one of the essential System design topics or concepts for programmers to know.

By the way, if you are preparing for System design interviews and want to learn System Design in depth then you can also checkout sites like ByteByteGo, InterviewKickStart, Design Guru, Exponent, Educative, Codemia.io, Bugfree.ai and Udemy which have many great System design courses

how to answer system design question

P.S. Keep reading until the end. I have a free bonus for you.

What is Caching in Software Design?

At its core, caching is a mechanism that stores copies of data in a location that can be accessed more quickly than the original source.

By keeping frequently accessed information readily available, systems can respond to user requests faster, improving overall performance and user experience.

In the context of system design, caching can occur at various levels, including:

  1. Client-Side Caching
    The client (user's device) stores copies of resources locally, such as images or scripts, to reduce the need for repeated requests to the server.

  2. Server-Side Caching
    The server stores copies of responses to requests so that it can quickly provide the same response if the same request is made again.

  3. Database Caching
    Frequently queried database results are stored in memory for faster retrieval, reducing the need to execute the same database queries repeatedly.

Here is a diagram which shows the client side and server side caching:

server side vs client side caching on system design

9 Caching Strategies for System Design Interviews

Understanding different caching strategies is crucial for acing technical interviews, especially for roles that involve designing scalable and performant systems. Here are some key caching strategies to know:

1. Least Recently Used (LRU)

This type of the cache is used to Removes the least recently used items first. You can easily implement this kind of cache by tracking the usage of each item and evicting the one that hasn't been used for the longest time.

If asked in interview, you can use doubly linked list to implement this kind of cache as shown in following diagram.

Though, in real world you don't need to create your own cache, you can use existing data structure like ConcurrentHashMap in Java for caching or other open source caching solution like EhCache.

Least Recently Used (LRU) caching strategy

2. Most Recently Used (MRU)

In this type of cache the most recently used item is removed first. Similar to LRU cache, it requires tracking the usage of each item and evicting the one that has been used most recently.

3. First-In-First-Out (FIFO)

This type of cache Evicts the oldest items first. If asked during interview, you can use use a queue data structure to maintain the order in which items were added to the cache.

First-In-First-Out (FIFO)

4. Random Replacement

This type of cache randomly selects an item for eviction. While this type of cache is simpler to implement, but may not be optimal in all scenarios.

5. Write-Through Caching

In this type of caching, Data is written to both the cache and the underlying storage simultaneously. One advantage of this type of caching is that it ensures that the cache is always up-to-date.

On the flip side write latency is increased due to dual writes.

Write-Through Caching

6. Write-Behind Caching (Write-Back)

In this type of caching, Data is written to the cache immediately, and the update to the underlying storage is deferred.

This also reduces write latency but the risk of data loss if the system fails before updates are written to the storage.

Here is how it works:

Write-Behind Caching (Write-Back) cache working

7. Cache-Aside (Lazy-Loading)

This means application code is responsible for loading data into the cache. It provides control over what data is cached but on the flip side it also requires additional logic to manage cache population.

Cache-Aside (Lazy-Loading) working

Cache Invalidation

Along with caching and different caching strategies, this is another important concept which a Software engineer should be aware of.

Cache Invalidation removes or updates cache entries when the corresponding data in the underlying storage changes.

The biggest benefit of cache invalidation is that it ensures that cached data remains accurate, but at the same time it also introduces complexity in managing cache consistency.

And, here is a nice diagram from DeisgnGuru.io which explains various Cache Invalidation strategies for system design interviews

top 3 Cache Invalidation strategies

Global vs. Local Caching

In global caching, a single cache is shared across multiple instances. In local caching, each instance has its own cache. One of the advantage of Global caching is that it promotes data consistency and Local caching reduces contention and can improve performance.

Global vs. Local Caching

Best System Design Interview Resources

And, here are curated list of the best system design books, online courses, 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.

  1. ByteByteGo: A live book and course by Alex Xu for System design interview preparation. It contains all the content of the System Design Interview book volumes 1 and 2, and will be updated with volume 3, which is coming soon.

  2. Codemia.io: 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 also a proper structure to solve them.

  3. Bugfree.ai: Thisi is another popular platform for technical interview preparation. It contains AI-based mock interviews as well as Interview experience and more than 3200+ real questions on System Design, Machine Learning, and other topics for practice =.

  4. DesignGuru's Grokking System Design Course: An interactive learning platform with hands-on exercises and real-world scenarios to strengthen your system design skills.

  5. "System Design Interview" by Alex Xu: This book provides an in-depth exploration of system design concepts, strategies, and interview preparation tips.

  6. "System Design Primer" on GitHub: A curated list of resources, including articles, books, and videos, to help you prepare for system design interviews.

  7. Educative's System Design Course: An interactive learning platform with hands-on exercises and real-world scenarios to strengthen your system design skills.

  8. High Scalability Blog: A blog that features articles and case studies on the architecture of high-traffic websites and scalable systems.

  9. YouTube Channels: Check out channels like "Gaurav Sen" (ex-Google engineer and founder of InterviewReddy.io and "Tech Dummies" for insightful videos on system design concepts and interview preparation.

  10. "Designing Data-Intensive Applications" by Martin Kleppmann: A comprehensive guide that covers the principles and practices for designing scalable and reliable systems.

  11. Exponent: 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 FAANG interviews.

how to prepare for system design

image_credit - ByteByteGo

Conclusion:

That's all about caching and different types of cache a Software engineer should know. As I said, Caching is a fundamental concept in system design, and a solid understanding of caching strategies is crucial for success in technical interviews.

Whether you're optimizing for speed, minimizing latency, or ensuring data consistency, choosing the right caching strategy depends on the specific requirements of the system you're designing.

As you prepare for technical interviews, delve into these caching strategies, understand their trade-offs, and be ready to apply this knowledge to real-world scenarios.

Bonus
As promised, here is the bonus for you, a free book. I just found a new free book to learn Distributed System Design, you can also read it here on Microsoft --- https://info.microsoft.com/rs/157-GQE-382/images/EN-CNTNT-eBook-DesigningDistributedSystems.pdf

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