A document database, also known as a document-oriented database or a JSON database, is a type of NoSQL database that stores and manages data in the form of documents. These documents can be in various formats such as JSON, BSON, XML, and YAML. Each document can contain different fields and structures and can be more flexible than traditional relational databases.
Document databases are ideal for unstructured data types and large-scale data storage, making them a popular choice for content management, e-commerce, social media, and log files. They are characterized by high scalability, high performance, and easy development of applications.
An example of a document database is MongoDB, a popular and widely used NoSQL document database. It stores data in flexible JSON format, making it easy to build and maintain complex applications. MongoDB is used by many companies such as eBay, Forbes, and Cisco.
NoSQL database: Document database is a type of NoSQL database that stores data in a JSON-like format.
Flexible data model: Document databases provide a flexible data model, which allows for storing and manipulating data in various formats.
Scalable and distributed architecture: They are designed to handle large amounts of data in a distributed environment, making them highly scalable.
Fast read and write operations: Document databases provide fast read and write operations, making them suitable for real-time data applications.
Document-centric approach: They use a document-centric approach that allows for the storage of related data in a single document.
No schema required: Unlike traditional relational databases, document databases do not require a schema, which makes it easier for developers to store and retrieve data.
Support for secondary indexes: Document databases support secondary indexes, which allows for fast querying and search of data.
ACID compliance: Some document databases are ACID compliant, meaning that they provide transaction support, ensuring data consistency and integrity.
Cloud-friendly: Document databases are designed to run in the cloud, making it easy to use and manage at scale.
Widely used: Many companies use document databases, including MongoDB, Couchbase, and Amazon DocumentDB.
What is a key-value store in a document database?
A key-value store is a data model in a document database where each document is represented as a key-value pair. The key is a unique identifier for the document, and the value is the data associated with that document.
What is sharding in document databases, and what advantages does it offer?
Sharding is a technique used to distribute data across multiple nodes in a distributed system. In document databases, sharding allows for horizontal scalability and improved performance by spreading the data and workload across multiple machines instead of relying on a single server.
How are indexes used in document databases, and what benefits does indexing offer?
Indexes in document databases are used to speed up query performance by quickly locating data that matches the query criteria. They work by storing a sorted representation of the data, allowing for faster access and reducing the amount of data that needs to be scanned.
What is denormalization in document databases, and how does it impact performance?
Denormalization is the process of duplicating data across multiple collections or documents in a document database, typically to improve performance by reducing the need for joins or aggregations. It can improve read performance but may increase storage costs and complexity.
How are transactions handled in document databases, and what limitations do they have?
Document databases typically support atomic operations on single documents, but transactional consistency across multiple documents is more challenging. Some document databases offer transaction support through features like snapshot isolation, but these solutions may have limitations such as reduced performance or complexity.