What are the differences between document-oriented and key-value NoSQL databases?

Document-oriented databases store data as documents, which are autonomous units of information that can have multiple fields, values, and structures. Documents are typically organized into collections, which are similar to tables in relational databases. Document-oriented databases are often used for applications that need to store and query complex, nested, or heterogeneous data, such as web content, social media, or e-commerce. Some examples of document-oriented databases are MongoDB, CouchDB, and Elasticsearch.

We selected MongoDB, a document-oriented NoSQL database, to handle product data in a retail project. Because each product was saved as a document, nested attribute querying was simple and the schema was flexible. Sales and customer satisfaction increased as a result of this strategy's improved customer recommendations and simplified inventory management.

We used Redis, a key-value NoSQL database, to handle real-time shipment status tracking in a logistics project. Every package had a special tracking number (key) that corresponded to its delivery status and current location (value). This made it possible to retrieve and update information quickly, guaranteeing accurate and timely delivery.

For example, Amazon DynamoDB is a a key-value database; Also widely used for in-memory caching, Redis is a good example of key-value database.

We used MongoDB, a document-oriented NoSQL database, to manage product catalogs in a retail project. Because of its adaptability, we were able to effectively store a variety of product data, such as prices, descriptions, and images. However, we used Redis, a key-value store, for user authentication and session management, choosing simplicity and speed over complicated data structures.

We chose to use MongoDB, a document-oriented database, for a logistics project in order to manage various shipment data, such as tracking numbers, addresses, and package specifics. We used Redis, a key-value store, for real-time tracking and status updates, which ensures fast and effective retrieval of basic but crucial data points.

We selected MongoDB for the management of product catalogs with a variety of attributes, including prices, images, and descriptions, in a retail project. Redis was used to manage customer sessions and real-time inventory updates, guaranteeing quick access to critical information like stock levels and user preferences.

Ao avaliar op??es de banco de dados NoSQL, leve em considera??o fatores como escalabilidade, desempenho, disponibilidade, facilidade de manuten??o e suporte à comunidade ou fornecedor