Basic Principles of Cache-Aside Pattern
The Cache-Aside Pattern is built on several basic principles that guide its implementation and use in system design. Here are the key principles:
- Lazy Loading: Data is loaded into the cache only when it is requested by the application. If the data is not present in the cache (a cache miss), it is fetched from the main database, and then stored in the cache for future access.
- Cache as a Separate Component: The cache is treated as a distinct layer, separate from the main database. The application interacts with both the cache and the database, deciding when to read from or write to the cache.
- Read-Through and Write-Through: The application reads data from the cache first. If the data is not found, it retrieves the data from the database, stores it in the cache, and then uses it. For write operations, the application updates the database directly. Cache invalidation or updates are handled as needed to ensure data consistency.
- Cache Eviction Policy: Since cache storage is limited, an eviction policy (such as Least Recently Used – LRU) is necessary to remove old or less frequently used data to make room for new data. This ensures that the cache remains efficient and relevant.
- Data Consistency and Expiry: Strategies must be in place to maintain data consistency between the cache and the database. This can include setting expiry times on cached data to ensure it is periodically refreshed or using cache invalidation techniques when data in the database changes.
- Performance Optimization: The primary goal is to optimize performance by reducing latency and the load on the database. By serving frequently accessed data from the cache, the system can respond faster and handle more requests.
- Scalability: The pattern helps the system scale efficiently by distributing read loads between the cache and the database, thus enabling the system to handle increased traffic without a proportional increase in database load.
Cache-Aside Pattern
The “Cache-Aside Pattern” is a way to manage data caching to improve system performance. When an application needs data, it first checks the cache. If the data is there a cache hit, it is used right away. If not a cache miss, the application fetches the data from the main database, stores a copy in the cache, and then uses it. This pattern helps reduce database load and speeds up data retrieval. It’s commonly used to enhance the efficiency and scalability of applications by making frequently accessed data quickly available.
Important Topics for Cache-Aside Pattern
- What is the Cache-Aside Pattern?
- How it Improves System Performance?
- Basic Principles of Cache-Aside Pattern
- How Cache-Aside Works
- Cache Population Strategies
- Challenges and Solutions for Cache Invalidation
- Handling Cache misses, Errors, and Timeouts in Cache-Aside pattern
- Optimization techniques to enhance Cache-Aside pattern performance
- Scaling Cache Infrastructure
- Real-world Examples
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