Title: MongoDB Author: Kriko Published: Jun 1, 2023 Last modified: Jul 7, 2026 --- 1. [Home](https://kriko.io/) / 2. [Glossary](https://kriko.io/glossary) / 3. M Letter # MongoDB **MongoDB** is a document-oriented NoSQL database management system. First released in 2009, it was developed to store, query and manage large and evolving datasets. Instead of the tables and rows used in traditional relational databases, MongoDB organises [data](https://kriko.io/services/data-analysis-insight) into collections and documents. Current versions of MongoDB Community Server are source-available and licensed under the Server Side Public License. MongoDB stores [data](https://kriko.io/services/data-analysis-insight) as **BSON** documents, which use a structure similar to JSON. Documents consist of field-value pairs, and documents within the same collection do not have to contain identical fields. This flexible schema model can simplify development when an application's [data](https://kriko.io/services/data-analysis-insight) structure changes over time. However, appropriate [data](https://kriko.io/services/data-analysis-insight) modelling and validation rules are still required to maintain [data](https://kriko.io/services/data-analysis-insight) quality and application consistency. MongoDB supports equality, range and field-based queries, as well as indexes designed for text, geospatial and other [data](https://kriko.io/services/data-analysis-insight) types. Frequently queried fields can be indexed to improve [data](https://kriko.io/services/data-analysis-insight) retrieval performance. Its aggregation pipeline can also be used to filter, group, transform and prepare [data](https://kriko.io/services/data-analysis-insight) for analytical processes. However, unsuitable [data](https://kriko.io/services/data-analysis-insight) models and unnecessary indexes may increase storage consumption and negatively affect query performance. MongoDB provides high availability through its **replica set** architecture. Multiple servers within a replica set maintain copies of the same dataset, providing redundancy and supporting automatic failover. This structure can reduce the risk of service disruption and [data](https://kriko.io/services/data-analysis-insight) loss following a server or hardware failure. However, replication is not a substitute for a separate backup strategy, and regular database backups should still be maintained. MongoDB can use **sharding** to distribute large datasets and intensive workloads across multiple servers. Data is divided between shards according to a selected shard key, enabling horizontal scalability. Selecting an appropriate shard key is essential for distributing workloads evenly and maintaining efficient query performance. A poorly selected shard key may result in uneven data distribution, overloaded servers and slower queries. MongoDB can be used for web and mobile applications, content management systems, product catalogues, user profiles, IoT applications and real-time data processing solutions. Its flexible document model can create a more natural relationship between objects in application code and documents stored in the database. MongoDB can be deployed and managed within an organisation's own infrastructure or through the fully managed **MongoDB Atlas** service. The appropriate deployment model should be selected by considering data relationships, transaction requirements, security, cost and scalability. In summary, MongoDB is built around a document data model, replication and distributed scaling capabilities. Its flexible structure can support rapid application development, while replica sets improve availability and sharding supports horizontal scalability. However, MongoDB should not automatically be considered the appropriate solution whenever a relational database appears restrictive. The database should be selected according to the application's data structure, query patterns, consistency requirements and operational needs. ## Discover it in the dictionary ### Metadata Metadata is information used to describe, explain and provide context for other data. It can contain details about a data source's content, structure, origin,… ### Call to Action A Call to Action, commonly abbreviated as CTA, is a message, button, link or directional element used to guide users toward a specific action.… ### Session A session is a technical concept that refers to the period of interaction between a user and a website or application. 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