Understanding how temporary storage speeds up access to information. It works like a quick-access drawer for data you use often.

Caching Basics

This happens when the system successfully finds requested data in the quick storage. It results in a very fast response for the user.

The Data Hit

This occurs when the requested information is not in the quick storage. The system must then look in the slower, main database.

The Data Miss

Data is only put into the quick storage after someone asks for it. This keeps the cache from filling up with things no one uses.

Lazy Loading Method

The system saves new information to the quick storage and the main database at the same time. This ensures both places always have the same exact data.

Live Update Method

New data is saved to the quick storage immediately, but the main database is updated later. This makes saving information feel much faster to the user.

Delayed Saving Method

Information is saved directly to the main database while ignoring the quick storage. This is useful for data that isn't expected to be read again soon.

Direct To Database

The quick storage system is responsible for fetching missing data from the main database itself. The main application doesn't have to worry about the search process.

Automatic Retrieval Path

The system tries to guess what data will be needed soon and loads it early. This prevents the user from ever having to wait for a slow search.

Predictive Content Refill

A set of rules used to decide which old data to throw away when the storage is full. It makes room for new, more relevant information.

Cleaning Full Caches

The system removes data in the exact order it was first saved. The very first item added is the very first one to be deleted.

Discarding Oldest Items

The computer deletes the piece of information that hasn't been touched in the longest time. It assumes that if you haven't used it lately, you don't need it.

Least Recently Used

The system tracks how many times each item is accessed and deletes the ones used the least. This keeps the most popular items available.

Least Frequently Used

Every piece of data is given a timer that tells it when to delete itself. This ensures that information doesn't stay in the storage forever.

Automatic Expiration Dates

The problem where the quick storage shows old information while the main database has newer info. This can lead to users seeing incorrect or 'stale' details.

Outdated Data Risks

Manually removing items from the quick storage because the original source has changed. This is done to prevent people from seeing the wrong information.

Forceful Data Clearing

What happens when many people ask for the same missing item at the exact same moment. It can overwhelm the main database with too many requests.

Meet the LRU Strategy