Caching Strategies for NoSQL Databases: Concepts and Best Practices Quiz

Explore essential caching strategies used with NoSQL databases, including cache patterns, key concepts, and optimization techniques. This quiz helps reinforce your understanding of how caches improve database performance and reduce latency in NoSQL environments.

1. Cache Aside Pattern

   Which caching strategy is described by an application first checking the cache before loading data from the database and updating the cache if the data is not present?

   1. Cache-Aside
   2. Write-Through
   3. Cache Aside
   4. Pass-Through

   Explanation: The cache aside pattern involves the application checking the cache before querying the database and updating the cache when the data is retrieved from the database. Write-through and pass-through relate to writing data, not reading. The distractor 'Cache-Aside' is a typographical error and not a valid strategy name.

2. Write-Through Caching

   In a system using write-through caching, what happens when data is written to the database?

   1. Data is simultaneously written to both the cache and the database.
   2. Data is first written to the database, and the cache is updated later.
   3. Data is written only to the database.
   4. Data is written only to the cache and not the database.

   Explanation: Write-through caching ensures that whenever data is written, it is updated in both the cache and database at the same time, improving consistency. Writing only to cache, or updating the cache later, introduces inconsistencies. Writing only to the database ignores the purpose of the cache.

3. Read-Through Caching

   What best describes a read-through cache in a NoSQL environment?

   1. The application updates the cache manually after every database read.
   2. All reads bypass the cache and go directly to the database.
   3. Only write operations are handled through the cache.
   4. The cache automatically loads missing data from the database when needed.

   Explanation: Read-through caching allows the cache itself to fetch and store a missing item when requested, simplifying the application logic. Option B incorrectly places this responsibility on the application. Bypassing the cache entirely or using the cache only for writes ignores the read-through pattern’s core functionality.

4. Cache Invalidation Triggers

   Which of the following actions typically requires cache invalidation to maintain data consistency?

   1. Compressing cache content
   2. Checking cache size limits
   3. Updating records in the database
   4. Reading data from the cache

   Explanation: When a database record is updated, the corresponding cache entry may become stale and should be invalidated or refreshed to maintain consistency. Reading data, checking size limits, or compression do not by themselves require invalidating the cache.

5. Cache Expiry (TTL) Usage

   Why would you set a Time-To-Live (TTL) on cache entries in a NoSQL system?

   1. To prevent any data from ever being deleted
   2. To automatically remove outdated or infrequently used data
   3. To increase the permanent storage capacity of the cache
   4. To guarantee that every entry is refreshed every second

   Explanation: Setting a TTL ensures that stale or seldom-accessed data is periodically cleared, keeping the cache clean. Unlike storage capacity, TTL is not about expanding space, nor does it mean data is never deleted. Guaranteeing refresh every second is not the purpose of TTL.

6. Cache Stampede Prevention

   What is cache stampede, and which approach helps to prevent it in NoSQL environments?

   1. When many clients request a missing key at once; using randomized TTLs to stagger cache refreshes
   2. A data breach caused by the cache; using encryption for cache entries
   3. When cache and database have different schemas; mapping data formats
   4. Frequent cache evictions; increasing cache memory size

   Explanation: A cache stampede happens when numerous clients try to access data missing from the cache simultaneously, overwhelming the database. Staggering expirations using randomized TTLs helps reduce simultaneous refreshes. The other options are about unrelated issues like security, evictions, or data format mismatches.

7. Write-Back Caching

   Which statement about write-back caching is accurate in a NoSQL setup?

   1. All writes bypass the cache and go directly to the database.
   2. Data is immediately removed from the cache after every write.
   3. Data is written to the cache first and periodically synced to the database.
   4. The cache is only used for read operations, not writes.

   Explanation: Write-back caching collects changes in the cache to enhance write speed, then periodically applies them to the database. Immediate removal, bypassing the cache for writes, or limiting the cache only to reads are not characteristics of write-back caching.

8. Choosing Appropriate Cache Keys

   Why is selecting the right cache key crucial when caching objects in a NoSQL database?

   1. It compresses the data for faster access.
   2. It automatically removes expired cache entries.
   3. It ensures unique identification and efficient retrieval of cached data.
   4. It encrypts data for security in the cache.

   Explanation: Cache keys provide a unique reference to cached objects, which is important for quick and accurate retrieval. Encryption and compression relate to data security and storage size, not identification. Automatic removal of expired entries is managed by TTLs, not keys themselves.

9. Benefits of Caching Frequently Read Data

   What is the primary performance benefit of caching frequently read data in a NoSQL database application?

   1. It speeds up index rebuilding in the database.
   2. It reduces the number of direct accesses to the underlying database, lowering latency.
   3. It increases the chance of data loss during a crash.
   4. It forces all writes to go through the cache only.

   Explanation: By serving frequently read data from cache, applications decrease database load and improve response time. Increased risk of data loss is not a benefit, and writing only to cache could cause inconsistency. Index rebuilding is unrelated to caching read operations.

10. Negative Caching

    What is 'negative caching' in the context of NoSQL databases?

    1. Storing information about missing or non-existent data to avoid repeated database lookups
    2. Compressing large cache entries to save space
    3. Storing only the differences between objects in the cache
    4. Applying encryption to cache data to prevent negatives

    Explanation: Negative caching saves the result of a not-found query so repeated requests avoid hitting the database unnecessarily. Compressing entries and storing differences are not related to the concept. Encryption is about security, not about non-existent data.