MongoDB is a cross-platform, document-oriented database. Classified as a NoSQL database, MongoDB eschews the traditional table-based relational database structure in favor of JSON-like documents with dynamic schemas (MongoDB calls the format BSON), making the integration of data in certain types of applications easier and faster.
Big companies are already using MongoDB. On the other hand, several cities are using a system comprising mainly of MongoDB and Hadoop which help analyze data and make decisions in order to improve the quality of life for their citizens.
Originally developed as a component of a planned platform-as-a-service product, the company shifted to an open source development model in 2009, and the database has since been adopted as the backend software of numerous websites and services, including Craigslist, eBay and Foursquare.
- Store data of any type such as structured, semi-structured and polymorphic.
- Process large amount of information.
- Support current requirements of applications.
- Empowers enterprises to be more agile growing quickly.
- It is a document oriented database.
- It is flexible.
- Developers have same functionalities as compared to RDBMS.
Here are features of MongoDB:
#1 Document-oriented
Instead of taking up a business subject and breaking it into several relational structures, MongoDB can store the business subject in the minimal number of documents.
#2 Ad hoc queries
MongoDB provides support to field, range queries, regular expression searches. Queries can return specific fields of documents and user-defined JavaScript functions.
#3 Replication
MongoDB provides high availability with replica sets.
#4 Load balancing
MongoDB scales horizontally using sharding. The user chooses a shard key in order to determine the distribution of the data collected. The data is split into ranges (based on the shard key) and distributed throughout the multiple shards.
#5 File Storage
The storage engine is the primary component of MongoDB responsible to manage data. MongoDB provides a variety of storage engines which allows you to select the one that suits your application in the best possible manner.
#6 Aggregation
MapReduce can be utilized for batch processing of both data and aggregation operations. MongoDB provides three comprehensive ways of aggregation such as aggregation pipeline, the map-reduce function, and single purpose aggregation methods.
#7 Server-side JavaScript execution
JavaScript can be utilized in queries, aggregation functions, and directly sent to the database to be executed.
#8 Capped collections
MongoDB supports fixed-size collections called capped collections. This type of collection maintains insertion order.
#9 Sharding
MongoDB uses sharding, a method for storing data across multiple machines to support deployments with very large data sets and high throughput operations.
#10 Security
In order to maintain a secure MongoDB deployment, administrators need to implement controls to ensure that applications have access to the data only that is required. MongoDB lets administrators to implement restrictions for deployment.
Finally
MongoDB has been developed to perform fast (embedded documents), flexible (schema less), scalable, to minimize administrative tasks, and easy to learn. It comes with robust and high on performance tools for data analysis (aggregation framework).
Big companies are already using MongoDB. On the other hand, several cities are using a system comprising mainly of MongoDB and Hadoop which help analyze data and make decisions in order to improve the quality of life for their citizens.
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Anna Harris working as web content writer and a strategist for a major IT firm delivering the best hire web & mobile app developer services for all your varied business needs.
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Anna Harris working as web content writer and a strategist for a major IT firm delivering the best hire web & mobile app developer services for all your varied business needs.
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