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nosql-databases

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What is NoSQL Database?

  • Unlike traditional relational databases (RDBMS) that use structured tables and require a predefined schema, NoSQL databases provide flexibility, scalability, and high performance in handling large volumes of data that don’t fit well into the rigid, table-based structures of relational databases.

  • NoSql databases unlike relational dbs are “eventually consistent”, which means they do not follow ACID properties strictly instead focusing on speed and scalability.

  • Transactions involving multiple documents or collections may not be atomic unless explicitly supported (e.g., MongoDB 4.x and later support multi-document transactions).

    BASE properties

Instead of ACID, NoSQL databases typically embrace the BASE model (Basically Available, Soft state, Eventual consistency) for consistency and availability:

  • Basically Available: Ensures that the system is available for reads and writes even when some nodes or replicas are down.
  • Soft state: Implies that the system’s state can change over time, even without input (due to eventual consistency).
  • Eventual consistency: Guarantees that all replicas will eventually be consistent, but not necessarily immediately.

This approach favors scalability and availability over immediate consistency.

Key Features of NoSQL Databases:

  1. Schema-less Design: Data is stored without the need for a fixed schema, allowing each entry to have a different structure.
  2. Scalability: NoSQL databases are optimized for horizontal scaling (distributing data across multiple servers), making them suitable for large-scale, distributed applications.
  3. Flexible Data Models: Data can be stored as documents, key-value pairs, columns, or graphs, depending on the NoSQL type.
  4. Eventual Consistency: Many NoSQL databases prioritize availability and partition tolerance (from the CAP Theorem), offering eventual consistency instead of strong consistency like in relational databases.
  5. High Performance: NoSQL systems are built to handle high-speed read and write operations with low latency.

Types of NoSQL Databases:

  1. Document Stores: Store data as documents (typically in JSON or BSON format).
    • Example: MongoDB, Couchbase
  2. Key-Value Stores: Store data as key-value pairs.
    • Example: Redis, DynamoDB
  3. Wide-Column Stores: Store data in columns rather than rows.
    • Example: Cassandra, HBase
  4. Graph Databases: Store data as graphs with nodes, edges, and properties, ideal for managing relationships.
    • Example: Neo4j, ArangoDB

When to Use NoSQL:

  • When dealing with large amounts of unstructured or semi-structured data.
  • When scalability is a primary concern (handling massive datasets across distributed systems).
  • When flexibility is needed in the data model (e.g., schema changes over time).
  • When quick access to data (e.g., caching or real-time analytics) is needed.

Example Use-Cases:

  • Social Networks: Graph databases for modeling relationships between users.
  • E-commerce: Document stores for flexible product catalogs with varying attributes.
  • IoT Applications: Wide-column stores for handling time-series data.
  • Session Management: Key-value stores for storing session data in memory for fast access.

In essence, NoSQL databases offer a more adaptable and scalable approach compared to traditional relational databases, making them ideal for modern applications with diverse, rapidly changing data.

Graph View