Journey To Database World: Part 6 (Key-Value Pair Database - Redis As Example)

Other Parts of This Series:

• Part 5: Journey To Database World: Part 5 (NoSQL Key-Value Pair Database - DynamoDB As Example)
• Part 7: Journey To Database World: Part 7 (Document Database - MongoDB As Example)

Story:

Once upon a time, in the Kingdom of DataLand, there lived a wise wizard named Redis. Redis was known far and wide for his magical Treasure Chest. This chest was special because it could store and retrieve anything instantly, faster than any other chest in the entire kingdom. Also it store data with a key.

Redis’s Magic Treasure Chest is like a key-value database. Each item (key) has a value, and the value can be simple (like text) or complex (like lists, sets, or hashes). Redis works fast because everything is stored in memory, and it can handle all kinds of magical items.

What is a NoSQL Key-Value Database?

A NoSQL Key-Value Database is a simple, fast, and highly scalable type of database where data is stored as key-value pairs. Each key acts as a unique identifier (like an ID), and the value can be any type of data (string, number, JSON, binary, etc.).

Key-value databases are designed to be simple, fast, and efficient, often used in scenarios where ultra-low-latency reads and writes are required. Example: Redis.

How Does a Key-Value Database Work?

• Key: The unique identifier for a specific value.
• Value: The data associated with the key. The value can be a simple value (like a number) or a complex object (like a JSON document).
• Data Storage: Data is stored in a hash table format, where each key maps directly to its value.
• Operations: Basic operations include GET, PUT, and DELETE for retrieving, updating, and deleting data.

Redis Key-Value Pair Database

Redis (Remote Dictionary Server) is an open-source, in-memory, key-value store that can be used as a database, cache, and message broker. It is known for its speed, simplicity, and support for a rich set of data structures.

What Is Special In It?

• In-Memory Database: Data is stored in RAM, making it extremely fast.
• Single-Threaded: Uses an event-driven, single-threaded model to achieve high performance.
• Persistence: While it primarily works in-memory, Redis supports persistence using RDB (snapshotting) and AOF (Append-Only File) mechanisms.
• High Availability: Redis supports replication, failover, and clustering for high availability.

Redis Data Types

Unlike traditional key-value stores that only support simple key-value pairs, Redis supports a variety of data types. Each key can store different types of values, making Redis a versatile data store. Like:

• String: Simple string value (can be binary). Use case: Storing user profiles, caching HTML pages.
• List: Ordered list of strings. Use case: Message queues, recent logs, activity feeds.
• Set: Unordered collection of unique strings. Use case: Tags, unique user identifiers, leaderboards.
• Sorted Set (ZSet): Like a Set, but with a score for each member. Use case: Leaderboards, ranking systems, priority queues.
• Hash: Key-value pairs within a key (like a mini-dictionary). Use case: User profiles, objects with multiple fields.
• Bitmap: Bit-level operations on binary data. Use case: Analytics, tracking presence, feature flags.
• HyperLogLog: Probabilistic data structure for unique counts. Use case: Estimating unique website visitors.
• Geospatial: Store geographic data with latitude and longitude. Use case: Geo-location services, store locators.

Common Redis Commands

Each data type has its own set of commands to perform operations on it. Here are the most common operations:

(1) String Commands

• SET: Set the value of a key.

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SET user:1 "John Doe"    

• GET: Get the value of a key.

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GET user:1      

• INCR / DECR: Increment or decrement a value.

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SET counter 0 
INCR counter // counter = 1 
DECR counter // counter = 0        

• EXPIRE: Set a key to expire after a given time.

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SET session "abc123" 
EXPIRE session 3600 // 1 hour expiry        

(2) List Commands

• LPUSH / RPUSH: Insert elements to the left/right of a list.

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LPUSH tasks "Task1" "Task2" // tasks = [Task2, Task1] 
RPUSH tasks "Task3" // tasks = [Task2, Task1, Task3]        

• LPOP / RPOP: Remove elements from the left/right of a list.

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LPOP tasks // "Task2", tasks = [Task1, Task3] 
RPOP tasks // "Task3", tasks = [Task1]        

• LRANGE: Get elements from a range of indices.

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LRANGE tasks 0 -1 // Get all items in the list        

(3) Set Commands

• SADD: Add members to a set.

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SADD colors "red" "blue" "green"        

• SMEMBERS: Get all members of a set.

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SMEMBERS colors // ["red", "blue", "green"]        

• SISMEMBER: Check if a value is a member of the set.

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SISMEMBER colors "red" // 1 (true) 
SISMEMBER colors "yellow" // 0 (false)        

• SREM: Remove members from a set.

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SREM colors "blue"

(4) Sorted Set (ZSet) Commands

• ZADD: Add members with scores to a sorted set.

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ZADD leaderboard 100 "Alice" 200 "Bob" 150 "Charlie"        

• ZRANGE: Get members in a range (by index or score).

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ZRANGE leaderboard 0 -1 // ["Alice", "Charlie", "Bob"]        

• ZRANGEBYSCORE: Get members within a score range.

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ZRANGEBYSCORE leaderboard 100 200 // ["Alice", "Charlie", "Bob"]        

(5) Hash Commands

• HSET / HGET: Set and get a field in a hash.

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HSET user:1 name "John Doe" age "30" 
HGET user:1 name // "John Doe"        

• HGETALL: Get all fields and values in a hash.

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HGETALL user:1 // ["name", "John Doe", "age", "30"]        

• HDEL: Delete fields from a hash.

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HDEL user:1 age       

(6) Bitmap Commands

• SETBIT / GETBIT: Set or get bits at specific positions.

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SETBIT bitkey 0 1 
GETBIT bitkey 0 // 1        

(7) HyperLogLog Commands

• PFADD / PFCOUNT: Add unique elements to HyperLogLog and get the count.

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PFADD unique_visitors "user1" "user2" "user3" 
PFCOUNT unique_visitors // Approximate unique count        

(8) Geospatial Commands

• GEOADD: Add locations with latitude, longitude, and name.

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GEOADD locations 13.361389 38.115556 "Palermo" 15.087269 37.502669 "Catania"        

• GEODIST: Get distance between two locations.

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GEODIST locations "Palermo" "Catania" km        

Use Cases of Redis

1. Caching: Store frequently used data (like user sessions) to reduce DB queries.
2. Message Queues: Use lists (LPUSH/RPOP) to create message queues.
3. Leaderboards: Use ZSETs to store scores and ranks.
4. Analytics: Use HyperLogLog for approximate cardinality estimation.
5. Geo-Location: Use GEO commands for geospatial queries.
6. Distributed Locking: Use SET key value NX PX to implement distributed locks.
7. Rate Limiting: Use counters and expiration for API rate limiting.

Performance Tips

1. Memory Usage: Use Redis memory-optimized data types.
2. Eviction Policies: Set keys to expire using EXPIRE, and choose eviction policies (LRU, LFU, etc.).
3. Avoid Large Keys: Avoid large lists, sets, or hashes to prevent blocking commands.
4. Sharding: Use Redis Cluster to distribute the data across multiple nodes.
5. Replication: Use master-slave replication for redundancy.

Summary:

Redis is not just a simple key-value store. It supports powerful data structures and operations, making it a multi-purpose, in-memory, ultra-fast database. From caching, messaging, real-time analytics, to leaderboards and geo-location, Redis provides an extensive set of capabilities.