Key-Value Stores

1. Overview

Definition: Key-value stores are a type of NoSQL database that use a simple data model where each data item (value) is stored with a unique identifier (key).
Structure:
- Key: A unique identifier used to retrieve a value.
- Value: The actual data, which can be simple or complex (e.g. string, JSON, binary).
Characteristics:
- Schema-less: No predefined structure for the data.
- Scalability: Easily scalable to accommodate large volumes of data.
- Performance: Optimized for fast retrieval and storage operations.
Use Cases:
- Caching layers (e.g., Redis).
- Session storage in web applications.
- User profiles in social media applications.
Data Consistency Models:
- Eventual consistency.
- Strong consistency (depending on implementation).

Definition: Distributed key-value stores are designed to run across multiple nodes, enabling horizontal scalability and redundancy.
Architecture:
- Data is partitioned across various nodes to distribute load.
- Uses replication to ensure fault tolerance.
Characteristics:
- Availability: High availability even in the event of node failures.
- Scalability: Can add nodes easily to handle increasing loads.
Popular Examples:
- Cassandra: Highly available, partitioned row store.
- DynamoDB: Amazon’s fully managed NoSQL database service.
Data Consistency Strategies:
- Eventual consistency ensuring that, given enough time, all updates will propagate.
- Tunable consistency allows users to configure the level of consistency needed.
Use Cases:
- Real-time analytics applications that require rapid access to high volumes of data.
- Global applications needing data to be accessible across various geographic locations.