![]() ![]() Systems with evolving data storage needs, demand for faster logging and caching, and changing designs.Modernizing payment architecture and legacy modernization.Scalable and high-performance video games.Ecommerce product catalogs and asset management.Maintaining geospatial or location-based data.Data storage for web and mobile applications.Content management systems like WordPress to enter, store, and edit content.MongoDB is used in thousands of organizations worldwide for data storage or as their applications’ database service. Capped collections: MongoDB supports capped collections, the collection type that handles data insertion order.The map function groups data by key-value, while the reduce function performs operations on it. Map-reduce function: This is used for batch data processing to bring aggregated results.Single-purpose aggregation: This is used to aggregate documents out of one collection.Aggregation pipeline: This offers better aggregation performance than others for most operations.Aggregation: Data aggregation allows users to get similar results to those obtained for the SQL clause - GROUP BY.MongoDB also lets developers manipulate files and content. GridFS, or grid file system, includes MongoDB drivers, and you can access it with Nginx and lighttpd plugins or the mongofiles utility. File storage: You can use MongoDB as a file system, known as GridFS, that comes with data replication and load balancing features for multiple computers to store files.This helps reduce the load on each server, ensures data uptime and consistency, and allows for scalable applications. Load balancing: MongoDB facilitates control concurrency to handle multiple client requests simultaneously to various servers.Each shard functions as an individual database, forming one single database using other shards contributes to load balancing and executes complicated queries. Here, users can choose a shard key (a master key with single or multiple replicas) to determine the data distribution in a collection and split the data into different ranges across shards. Sharding: MongoDB is capable of scaling horizontally with the help of sharding, a method of distributing large datasets across different data collections.You can update these ad-hoc queries in real time with the help of MongoDB Query Language (MQL), which is useful for real-time analytics for enterprises. Also, queries include JavaScript functions defined by users and can return specific document fields. ![]() That said, MongoDB supports range query, regular expression (Regex), and field searches. Ad-hoc queries: Ad-hoc queries are temporary commands that provide different returns for executing queries.This helps improve search performance in the database and lets you perform the search on indexes rather than the entire document, which automatically helps increase search speed. Indexing: You can index fields in MongoDB documents as primary or secondary.In case of a server failure, you can always retrieve your data from the copies stored in other servers. This feature is helpful for data backups and disaster management. Replication: MongoDB allows you to make several copies of your data using replication ( replica sets) and deploy them on various servers.Now, let’s move on to looking at some of the main features of MongoDB: MongoDB or MySQL? □ Which database management system is right for you? □ Click to Tweet Features of MongoDB As a result, it facilitates higher speed and storage requirements. MongoDB offers greater security, reliability, and efficiency in addition to the flexibility of modifying the data structure or schema. The key/value pairs can be structured differently from one document to another. These documents contain a series of value or key pairs of different types, such as nested documents and arrays. Instead of storing data in rows and columns, MongoDB takes a document-oriented design that represents data in various JSON-like documents and collections. MongoDB differs from traditional database systems in terms of how that data gets stored.
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