MongoDB is a document-based database known for its document-oriented data model, flexible schema, and scalability. It is suitable for processing large amounts of unstructured or semi-structured data, such as social media data and the Internet of Things. Sensor data, e-commerce catalogs and media content.
MongoDB Database: Document Database
Introduction to MongoDB
MongoDB is an open source multi-document database known for its document-oriented data model and flexible schema. This database is designed to handle large amounts of unstructured or semi-structured data.
Document-based database
Different from traditional SQL databases, MongoDB uses a document-based data model. A document is a collection of JSON documents consisting of key-value pairs. These documents allow for the embedding of complex nested data such as arrays and embedded documents.
Features and Benefits
- Flexible Schema: MongoDB allows you to create and modify schemas at runtime. This does not work with SQL databases, where the schema is fixed at table creation time.
- Document orientation: MongoDB stores data as documents instead of splitting data into rows and columns, which simplifies querying and operating on complex data.
- Scalable: MongoDB can be scaled horizontally through replica sets and sharded clusters to handle large amounts of data and concurrent loads.
- High Availability: Replica sets ensure data redundancy and failover, while sharded clusters improve scalability and performance.
- Easy to integrate: MongoDB provides drivers for various programming languages, making it easy to integrate with applications.
Use Cases
MongoDB is suitable for processing the following types of data:
- Social media data (such as posts and profiles)
- IoT sensor data
- Website analytics data
- E-commerce catalog
- Media content (such as pictures and videos)
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