MongoDB is an open source NoSQL database management program. NoSQL is used as an alternative to traditional relational databases. NoSQL databases are quite useful for working with large sets of distributed data.

Why Use MongoDB And When To Use It

MongoDB is a great database for integrating geospatial data with other types of data. For example, if “location” is a piece of metadata that you’re working with, MongoDB supports GeoJSON types, so you can efficiently store latitude and longitudes. Furthermore, MongoDB supports 2DSphere Indexes, which optimize geometric calculations on sphere. In SQL, tables consist of records/rows, in NoSQL, collections are documents.

What is MongoDB flexible storage architecture?

With single field indexes, the database engine can freely traverse the index either forwards or backwards. However, with compound indexes this is not always the case. If a particular sorting order for a combination of fields is queried more often, it can further increase performance to include that order in the index definition.

Why Use MongoDB And When To Use It

Notice that now IXSCAN is used against the newly created ascents.total_-1 index, and only four documents have been examined. This is the same number of documents returned and examined in the index, so no additional documents have been retrieved to complete the query. A server with a regular, non-root user with sudo privileges and a firewall configured with UFW.


Cloud-based storage needs to easily distribute data across multiple servers, which suits MongoDB’s nature perfectly. You can place data into a NoSQL database without requiring a predefined schema, so you can change the data model and formats without disrupting applications. MongoDB uses documents that can contain sub-documents in complex hierarchies making it expressive and flexible. MongoDB can map objects from any programming language, ensuring easy implementation and maintenance. So, if you want to make the most of that data, you need organized, easily accessible information.

Why Use MongoDB And When To Use It

MongoDB isn’t just suited for processing massive volumes of data – its strengths can apply to an application of any size that requires processing varied data types from various sources. Velocity refers to the speed at which data is generated and analyzed, which in Big Data’s case is often continuous and in real-time. For example, so much as a 10 second lag in tracking the path of a tsunami across interlocking waterways and infrastructure can be lethal if the wave is travelling at 80kmph. Huge volumes of data need to be converted into on-the-ground evacuation orders in real-time, not 60 seconds ago. Transactions are the key reason why MongoDB has rapidly crossed the chasm from niche software to market-disrupting mainstream database platform.

MongoDB vs. RDBMS: What are the differences?

This tutorial was validated using a server running Ubuntu 20.04, and you can prepare your server by following this initial server setup tutorial for Ubuntu 20.04. This means that it checks the input data against the schema you declared in the Tutorial model class. If the input data violates the schema or any of its constraints, then you get an exception, and the data isn’t saved into the database. By default, .save() inserts the new document into a collection named after the model class, Tutorial, except using lowercase letters. In this case, the collection name is tutorial, which matches the collection you’ve been using to save your tutorials. Each specific field type also has its own set of parameters.

In theory, each document in a collection can have a completely different structure or set of fields. If you’ve followed the installation and running instructions, then you should already have an instance of MongoDB running on your system. Now you can start creating and testing your own databases.

Delivering data in high-performance applications

Or a blogging application, where users want to log in and create/edit their own blogs. Users not interacting with each other is the key takeaway. With a relational database, one would have to store what is MongoDB information about a user across several tables. When that user logs on, the application would have to make several queries, or complex JOIN queries, to access all the information for that user.

Why Use MongoDB And When To Use It

Since NoSQL databases like MongoDB expand horizontally, you can scale by adding more machines to your resource pool. MongoDB was created in 2009 as an open-source, highly scalable, robust, and free NoSQL database. You may wish to consult the following resources for additional information on this topic.

MongoDB vs MySQL: What Are They?

You can check the documentation for a complete guide to the available field types. Here, you run a loop on the object that .find() returns and print successive results, using pprint.pprint() to provide a user-friendly output format. This statement is handy when the name of your database isn’t a valid Python identifier. For example, if your database is called rp-tutorials, then you need to use dictionary-style access.

  • The company also added support for multi-document atomicity, consistency, isolation, and durability transactions as part of MongoDB 4.0 in 2018.
  • If you are reading so far, you may think I am writing this post against MongoDB.
  • Instead, IXSCAN is present, indicating that the index was used as part of the query execution.
  • MySQL is an open-source, relational database management system that stores data in tables and rows.
  • Our application is made for desktops, and we started using MongoDB for that application.
  • Additionally, if you already have your setup, this article might be also interesting, as during the evaluation of a product some of the following topics can have passed unnoticed.

Furthermore, read or write takes place on the primary replica by default, and then you can replicate it on a secondary replica. In addition, replica sets are more robust and suitable for production usage. But when it comes to clustered databases, MySQL doesn’t support full-text indexing yet. Even if your developers are not skilled in MySQL but have experience with other SQL databases, they are likely to catch up quickly. Customer service and marketing companies can leverage this to conduct their social network research.

Step 4 — Creating an Index on an Embedded Field

If you need a robust, scalable, and flexible database solution, then MongoDB might be a good option for you. MongoDB is a mature and popular NoSQL database with great Python support. With a good understanding of how to access MongoDB with Python, you’ll be ready to create database applications that scale well and provide excellent performance. Just like relational databases need a primary key to uniquely identify every row in a table, MongoDB documents need to have an _id field that uniquely identifies the document.