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Key-Value Stores (Redis)

From MongoDB to Key-Value Stores

We've explored document databases with MongoDB. Today, we're stepping into the realm of Key-Value Stores, another fundamental data storage paradigm.

What are Key-Value Stores?

Key-Value stores are a type of NoSQL database that store data in a simple key-value pair format, where each key is associated with a single value.

Characteristics of Key-Value Stores

  • Simple data model
  • Fast read and write operations
  • Scalable and horizontally partitioned
  • Often used as caches or session stores

Advantages of Key-Value Stores

  • Simplicity and ease of use
  • High performance
  • Scalability and flexibility
  • Suitable for specific use cases (caching, session management)

Disadvantages of Key-Value Stores

  • Limited data modeling capabilities
  • Not suitable for complex queries
  • Data consistency challenges in certain scenarios

Data Structures in Key-Value Stores

  • Hash tables
  • B-trees
  • Radix trees
  • Log-structured merge trees

Common Key-Value Store Operations

  • Get (Retrieve value for a key)
  • Set (Add or update a key-value pair)
  • Delete (Remove a key-value pair)
  • Increment/Decrement (Atomically modify a numeric value)
  • Multi-Get/Multi-Set (Perform multiple operations in a single request)

Redis Overview

Redis is a popular open-source key-value store known for its speed, flexibility, and data structures support.

Redis Data Types

  • Strings
  • Hashes
  • Lists
  • Sets
  • Sorted Sets
  • Bitmaps

Redis Commands: Basic Commands

  • GET/SET
  • INCR/DECR
  • DEL
  • EXISTS
  • EXPIRE
  • TTL

Redis Commands: Data Structures Commands

  • HSET/HGET
  • LPUSH/RPUSH
  • SADD/SMEMBERS
  • ZADD/ZRANGE
  • BITOP

Redis Commands: Advanced Commands

  • PUBSUB
  • Transactions
  • Scripting
  • Geo commands
  • HyperLogLog

Redis Performance Considerations

  • Data structure selection
  • Key distribution
  • Caching strategies
  • Hardware optimizations
  • Monitoring and tuning

Redis Use Cases

  • Caching
  • Session management
  • Real-time messaging
  • Leaderboards
  • Counting and aggregation

Next Up: Graph Databases (Neo4j)

In the next session, we'll dive into the world of Graph Databases, specifically Neo4j. Graphs are a powerful data structure for representing relationships and connections. Follow us to learn why and how to use them!