Write-through pattern in Redis

Introduction

The write-through pattern helps keep data in the cache and database the same by saving data to both at the same time. This makes sure the cache always has the latest data.

When you want to speed up reading data by using a cache but keep data accurate.

When you update data often and want the cache to reflect changes immediately.

When you want to avoid stale or outdated data in your cache.

When your application reads data more often than it writes.

When you want simple and reliable cache management without complex invalidation.

Syntax

Redis

1. Write data to the database.
2. Write the same data to the cache (Redis).

Example commands:
SET key value  # Redis command to save data
-- plus your database update command

The write-through pattern means writing to the database first, then to the cache.

If the database write fails, do not update the cache to avoid inconsistency.

Examples

Save user data in Redis cache and database at the same time.

Redis

SET user:1 "Alice"
-- Also update user with ID 1 in your database

Write product info to both Redis and database to keep them synced.

Redis

SET product:100 "Laptop"
-- Update product 100 details in your database

Sample Program

This example shows updating a user's name in the database first, then saving the same data in Redis cache with the key 'user:2'.

Redis

-- Simulate write-through pattern
-- Step 1: Update database (simulated here as a comment)
-- UPDATE users SET name = 'Bob' WHERE id = 2;

-- Step 2: Write to Redis cache
SET user:2 "Bob"

Important Notes

Always write to the database first to ensure data is saved permanently.

If writing to Redis fails, you can retry or handle the error, but the database remains the source of truth.

This pattern helps keep cache and database data consistent automatically.

Summary

Write-through pattern saves data to both database and cache at the same time.

It keeps cache data fresh and avoids stale reads.

Use it when you want simple, reliable cache updates on every write.

Practice

1. What is the main purpose of the write-through pattern in Redis caching?

easy

A. To delete data from the cache when the database is updated

B. To update only the cache and delay database writes

C. To read data only from the cache without updating the database

D. To update both the cache and the database at the same time

Solution

1. Step 1: Understand write-through pattern basics

   The write-through pattern means writing data to the cache and database simultaneously to keep them in sync.

2. Step 2: Identify the correct behavior in Redis context

   In Redis, this pattern ensures cache is updated immediately when the database changes, avoiding stale data.

3. Final Answer:

   To update both the cache and the database at the same time -> Option D

4. Quick Check:

   Write-through = update cache + database [OK]

Hint: Write-through updates cache and DB together [OK]

Common Mistakes:

• Thinking write-through updates only cache
• Confusing write-through with write-back pattern
• Assuming cache is updated after database asynchronously

2. Which Redis command sequence correctly implements a write-through cache update when saving a user profile with key user:123 and value {"name":"Alice"}?

easy

A. DEL user:123 then SET user:123 '{"name":"Alice"}'

B. GET user:123 then SET user:123 '{"name":"Alice"}'

C. SET user:123 '{"name":"Alice"}' followed by DB update

D. SET user:123 '{"name":"Alice"}' only, no DB update

Solution

1. Step 1: Identify write-through steps

   Write-through requires writing to cache (Redis) and database together.

2. Step 2: Match Redis commands to write-through

   Using SET updates Redis cache; followed by DB update ensures both are in sync.

3. Final Answer:

   SET user:123 '{"name":"Alice"}' followed by DB update -> Option C

4. Quick Check:

   SET + DB update = write-through [OK]

Hint: SET cache then update DB for write-through [OK]

Common Mistakes:

• Only updating cache without DB
• Deleting cache before setting without DB update
• Getting cache before setting without DB write

3. Consider this pseudo-code using write-through pattern:

cache.SET('item:1', 'value1')
database.UPDATE('item:1', 'value1')
result = cache.GET('item:1')

What will result contain after execution?

medium

A. null

B. 'value1'

C. Old cached value

D. Error due to missing database read

Solution

1. Step 1: Analyze cache write

   The cache is set to 'value1' for key 'item:1' before database update.

2. Step 2: Analyze cache read

   Reading from cache immediately after setting returns the new value 'value1'.

3. Final Answer:

   'value1' -> Option B

4. Quick Check:

   Cache GET after SET returns new value [OK]

Hint: GET after SET returns updated cache value [OK]

Common Mistakes:

• Assuming cache GET returns null if DB updated
• Thinking old cached value remains after SET
• Expecting error without explicit DB read

4. You implemented write-through caching but notice stale data in Redis after database updates. Which mistake likely causes this?

medium

A. Updating database but forgetting to update Redis cache

B. Updating Redis cache but not the database

C. Using GET instead of SET to update cache

D. Deleting database entries without clearing cache

Solution

1. Step 1: Identify cause of stale cache

   If database updates but cache is not updated, cache holds old data causing staleness.

2. Step 2: Match mistake to write-through pattern

   Write-through requires cache update on every DB write; missing cache update breaks this.

3. Final Answer:

   Updating database but forgetting to update Redis cache -> Option A

4. Quick Check:

   Missing cache update causes stale data [OK]

Hint: Always update cache when DB changes [OK]

Common Mistakes:

• Updating cache only without DB
• Using GET to update cache instead of SET
• Not clearing cache on DB deletes

5. You want to implement a write-through cache in Redis for a product catalog. Which approach best ensures data consistency and minimal stale reads?

hard

A. On product update, update both Redis cache and database synchronously in the same operation

B. On product update, update the database first, then delete the Redis cache entry

C. On product update, update only the database and rely on cache expiration to refresh

D. On product update, write to Redis cache first, then update the database asynchronously

Solution

1. Step 1: Understand write-through consistency needs

   Write-through requires cache and database to be updated together to avoid stale reads.

2. Step 2: Evaluate options for consistency

   Updating both synchronously ensures cache always reflects latest DB state, minimizing stale data.

3. Final Answer:

   On product update, update both Redis cache and database synchronously in the same operation -> Option A

4. Quick Check:

   Synchronous cache + DB update = consistent write-through [OK]

Hint: Update cache and DB together synchronously [OK]

Common Mistakes:

• Updating cache before DB asynchronously causing race conditions
• Deleting cache instead of updating it
• Relying only on cache expiration for freshness