MongoDB: After relational database management, we have seen the rise of NoSQL, and now it has reached the introduction of NewSQL, which offers the benefits of both SQL and NoSQL. There had been many databases in all these segments. Some remained on top of the enterprise database choices, whereas others just came and gone as such.
All business enterprises are now seeking more and more innovations in database management by developing the most cost-effective method of storage, manipulation, and analysis of data. This also paved the way for the upbringing of many data management and analytical tools. Among the top NoSQL databases, which stayed stable overtime, MongoDB is one of the enterprise database users’ favorite choices.
Table of Contents
What is MongoDB?
MongoDB is an open-source solution in database administration, which follows an innovative document-centered DBMS model. MongoDB is primarily an unstructured data query language, which is also very powerful in NoSQL database management. MongoDB is different from the relational models of tables with rows and columns. NoSQL generally, and DB especially follows a different architecture to build documents and collection data.
The primary unit of NoSQL DB is the data unit, which contains a unique key-value pair set. This will let the database documents take data of various structures and with different fields. The storage format of MongoDB is BSON, which is a binary system for JSON documents. MongoDB data model is very elastic and allows you to combine different data sets and store data types without compromising validation rules, indexing options, and data access. This means there is no downtime in case you are trying to modify your data schemes.
Components of MongoDB
MongoDB can be considered a data container, and each of the databases inside DB has unique sets of files, and there can be multiple DBs with unique file systems inside it.
- Collection – Collection in MongoDB is a set of documents. In relational database management systems, the collection is referred to as a table. As a while, collection exists inside the database, and inside a collection, there are many documents with further sub-fields. However, all these documents are within a specific collection, which all are for the same purpose.
- Document – It is the combination of many key-value pairs as the primary data units. DB documents are tied to dynamic schemas, the advantage of which is that each of the documents in the given collection may not have the same structure and fields inside it. Common fields in collection documents may have different data types.
- Queries – There are ad-hoc queries and document-based queries, which both are supported on DB.
- Replication – Master-slave replication is made much easier in DB.
- Index support – Unlike the relational database management systems, in MongoDB, we can directly index any fields in the document to make things easier.
- Multiple servers – The databases can simultaneously run-on multiple servers. In case of any failover, the data can also be duplicated as being hosted on multiple servers.
Failure handling is also much easier on MongoDB, with a large number of replicas being created. It can also ensure protection against any machine failures, rack failures, or bigger data center failures. For MongoDB implementation and support, you can take the assistance of RemoteDBA.com as a reliable provider.
Compared to the relational database models, here are some distinctive features of MongoDB.
- Ease of use
- So lightweight.
- Much quicker
- Ideal in big data and complex unstructured data environments.
- Mobile with social infrastructure
- Easy content management.
- Easy user data management
Higher-level features of MongoDB are:
- It is a schema-less DB, and each collection in MongoDB may hold many documents.
- There can be distinguishable differences between the number of fields, content, and size of the documents from one another.
- The structure of each object is clearer in MongoDB compared to relational DBs.
- No complex joins out there in Mongo DB.
- MongoDB offers a deep query facility as it can support powerful dynamic querying on documents.
- MongoDB is very easy to scale up and down based on the user needs.
- The internal memory of MongoDB for storing working sets is much easier to access.
Comparison among MongoDB and RDBMS
In RDBMS, the tables are used as storing parameters, while in DB, the collection is used for sorting. In the relational model, there are multiple schemas and, in each schema, tables are created to store data. In contrast, MongoDB is document-oriented, where data is written in BSON format, a JSON-like format. DB is also much faster than the traditional RDBMS. A side-by-side comparison of MongoDB with RDBMS is below.
|Key-value pair collection
|Easy to set up
|Demands expert setup
|Possess dynamic schemas
|Possesses predefined schema
DB overrides many of the shortfalls in conventional database management systems, like the need for scalability. As various business systems need to upgrade their DBMS systems more frequently based on the changing requirements, scalability is a big challenge. As DB offers exceptional scalability, it is easier for the users to facilitate more data accommodation and integration. DB also has no downtime when applications are scaled. Graph processing and text searching features are also enabled on MongoDB.
Unlike the conventional SQL databases, MongoDB can also store data in JSON documents, ensuring data persistence. The application objects are mapped to the document model, making it easier to control and manipulate data. Mongo DB’s specific schema enables better governance, too, in terms of data access and indexing.
Along with administrators and database developers, operational teams can also enjoy a better job with DB as it is offering cloud support. The overall cost of implementing and managing DB is largely lesser, and it offers more on-demand pricing subscription models, too, along with unrelenting support. Overall, Mongo is a reliable and comprehensive database package for growing organizations to leverage modern technologies’ benefits, too, like Big Data, Artificial Intelligence, Business Analytics, and the Internet of Things, etc.