Why Use MongoDB? Advantages & Use Cases DEV Community

September 16, 2022 • Posted by Toby Magcaling in Software development •  

Traditionally, database management systems organize data based on the relational model. As organizations’ data needs have changed, however, a number of new types of databases have been developed. Adoption of NoSQL databases has primarily been driven by uptake from developers who find it easier to create various types of applications compared to using relational databases. Without the right indexes, a database is forced to scan documents one by one to identify the ones that match the query statement. But if an appropriate index exists for each query, user requests can be optimally executed by the server.

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This is what we call a “flexible schema.” This flexibility allows developers to iterate faster and migrate data between different schemas without any downtime. However, if you want to lock down your schema at a certain point, you can do so by applying validation rules to your collections. MongoDB (MDB 1.31%) made a name for itself by upending the traditional database. This provides users with a much more robust database solution and also helps developers facilitate the creation of software and apps.

The amount of time that RDMSs have been around also means there is wide support available, from tools to integration with data from other systems. Relational databases are also the best choice if relationships between entities are important. However, this simplicity restricts the type of use cases it can be used for. Below is the query to get the product name and price of the given productid using the Mongo Query API (similar to SQL in the previous section). In this query, the first argument (_id) represents the filter to use on the collection, and the second one—the projection—fields that should be returned by the query. In this case, however, we are able to view all the data of one customer in a single place as a single document.

MongoDB supports transactions

However, compared to relational databases, wide-column databases are much slower when handling transactions. Columns group together similar attributes rather than using rows and store these in separate files, which means transactions have to be carried out across multiple files. Graph databases are the most specialized of the non-relational database types. They use a structure of elements called nodes that store data, and edges between them contain attributes about the relationship. RDMS, or SQL databases, have been around for so long that a wide variety of tools and resources have been developed to help get started and interact with relational databases. The English-like syntax of SQL also makes it possible for non-developers to generate reports and queries from the data.

It is an open-source document-based tool used for high-volume data storage. Most NoSQL databases have a strong community of developers surrounding them. This means that there is an ecosystem of tools available and a community of other developers with which to connect.

Connect to a MongoDB Server from C# Code

Companies and development teams of all sizes and industries recommend MongoDB regardless of its various pros and cons. Bosch, Barclay, Morgan Stanley, etc are just a few of their major clients. Businesses should understand the pros that MongoDB offers and the cons that it possesses.

Sharding is the process of dividing data from a large set and distributing it to multiple servers. MongoDB offers a simple query syntax that is much easier to grasp than SQL. It provides an expressive query language that users find postgresql document database helpful during development. MongoDB is built on a scale-out architecture that allows developers to build applications using agile methods. It is popular among developers as it helps them build internet and business applications.

MongoDB with .NET

With more than 15 million downloads, MongoDB has become the most preferred database and is used by programmers globally. Keep on reading to know more about MongoDB, its advantages, why to use it, and where it can be used. Although MongoDB is a great database, there are times when you should and shouldn’t use it. Applications get the power and responsibility to interpret different properties found in a collection’s documents. MongoDB was created in 2009 as an open-source, highly scalable, robust, and free NoSQL database.

By reading this article, you’ll have gained a better understanding of the features that set MongoDB apart from other database management systems. Although MongoDB is a powerful, flexible, and secure database management system that can be the right choice of database in certain use cases, it may not always be the best choice. While its document-based and schemaless design may not supplant the relational database model any time soon, Mongo’s rapid growth highlights its value as a tool worth understanding. Structured Query Language or SQL is a domain-specific language used for managing relational databases.

Database

Relational databases store data in structured tables that have a predefined schema. To use relational databases, a data model must be designed and then the data is transformed and loaded into the database. NoSQL databases were created in response to the limitations of traditional relational database technology. When compared to relational databases, NoSQL databases are often more scalable and provide superior performance. In addition, the flexibility and ease of use of their data models can speed development in comparison to the relational model, especially in the cloud computing environment.

• It provides an expressive query language that users find helpful during development.
• However, the striking features you get for using MongoDB should not be sacrificed for the high-memory cost.
• Businesses should understand the pros that MongoDB offers and the cons that it possesses.
• MongoDB was created in 2009 as an open-source, highly scalable, robust, and free NoSQL database.
• Another characteristic of MongoDB that has helped drive its adoption is the flexibility it provides when compared with more traditional database management systems.

At the end of the day, optimal load balancing remains one of the holy grails of large-scale database management for growing enterprise applications. Properly distributing millions of client requests to hundreds or thousands of servers can lead to a noticeable (and much appreciated) difference in performance. Time series data is most commonly generated by a device, such as a sensor, that records data over time.

Are you moving other aspects of your business to the cloud?

This is why MongoDB, a document-oriented, flexible schema database, stands apart as the cloud database platform of choice for enterprise applications that require real-time analytics. With ad-hoc query support that allows developers to update ad-hoc queries in real time, the improvement in performance can be game-changing. Using Structured Query Language databases, every time there is an attempt to insert information, declaration and confirmation of a table schema are necessary. MongoDB, being a document database, holds different documents in a single collection. Simply put, MongoDB allows the storage of multiple objects in a unified way, with a different set of fields.