A [[Document Database]] is a type of [[NoSQL]] database that stores data in a document-oriented format. Instead of using tables and rows like traditional relational databases, document databases use JSON or XML-like documents to represent and organize data. Examples of [[Document Database]] include MongoDB, CouchDB, and Amazon DocumentDB. Features of Document Databases: 1. Flexible Schema: Unlike relational databases that require predefined table structures, document databases allow for dynamic schemas. This means that each document can have its own unique structure, allowing for greater flexibility when storing different types of data. 2. Scalability: Document databases are designed to scale horizontally by distributing data across multiple servers. They can handle large amounts of data and high traffic loads efficiently. 3. Querying Flexibility: Document databases support powerful querying capabilities using various query languages like MongoDB's Query Language (MQL). They allow for complex queries, including nested fields and arrays within documents. Strengths of Document Databases: 1. Schema Flexibility: The flexible schema allows for easy adaption to changing requirements without the need for expensive migrations or downtime. 2. High Performance: Due to their ability to distribute data across multiple servers, document databases can provide high-speed read and write operations even under heavy workloads. 3. Scalability: Document databases excel at horizontal scalability, making them suitable for handling big data applications with growing datasets. Weaknesses of Document Databases: 1. Lack of Relationships: Unlike relational databases where relationships between tables are explicitly defined, document model databases do not have built-in support for relationships between documents. Handling complex relationships can be challenging and may require additional application logic. 2. Data Redundancy: As each document can have its own structure, there may be redundant data duplication across multiple documents. This redundancy can lead to increased storage requirements but is often necessary to optimize query performance. 3. Limited Transaction Support: Most document model databases do not provide full ACID (Atomicity, Consistency, Isolation, Durability) transaction support. They typically support atomic operations within a single document but may lack transactional consistency across multiple documents. In summary, Document Databases offer flexibility, scalability, and high performance for handling unstructured or semi-structured data. However, they may lack built-in relationship support and have limited transaction capabilities compared to traditional relational databases.