What is MongoDB?

Jan 18, 2024 | Blog Post

We’re living in the information age. Consequently, data is the most valuable resource that we have. The most successful companies of the information age have been and will be those who can make the best use of this data.

Today’s amount of available data almost defies imagination; so vast that we’re talking about volumes in petabytes. A petabyte is the equivalent of 500 billion pages of text.

Origin of NoSQL

To efficiently handle this scale of data, a NoSQL database is essential. Unlike traditional relational databases, NoSQL databases excel in managing unstructured data, which is not only human-readable but also scalable to suit the extensive demands of large-scale enterprises.

NoSQL databases are tailored for specific data models. They diverge from the conventional structure of storing data in tables with rows and columns. Instead, data in NoSQL databases is stored in a JSON document format. This means each document encapsulates all the attributes for a given entry.

So what does that mean in layman’s terms?

In the “old days” a database was organized like a giant spreadsheet. It had column names at the top, and under each column, there were rows that represented each entry. So if, for example, the table contained a list of people, the columns might be “First Name, Last Name, Address, City, State, ZIP. Phone Number”. Each row would represent a person like “Smith, Nick, 350 Main Street, Springfield, MA, 01010, 205-555-1212”.

This data structure worked fine for databases of manageable size, but what would happen if you wanted to put every person in the world on that database? It would be hard to find anything, right?

In contrast, a NoSQL database employs what’s known as “sharding”, which means that chunks, or “shards” of the database can be maintained in different places. So in the above example, you might have one file with all the people with the last name “Smith” stored in one place, and all the files with the person with the last name “Lee” in another place. That way, you only need to access the exact data you need without having to scroll through billions of records.

This approach significantly enhances the database’s efficiency, ease of development, and scalability. Each document resides in a collection, and the simplicity and human-readable format of NoSQL databases make them particularly user-friendly and accessible.

What Exactly is MongoDB?

MongoDB is classified as a NoSQL database, renowned for its open-source, free-to-use, and cross-platform capabilities. Compatible with various operating systems like Linux, macOS, and Windows, MongoDB made its debut on February 11, 2009, courtesy of MongoDB Inc. The groundwork for this database, however, was laid in 2007 by 10gen Software.

Initially, MongoDB was conceptualized as a part of a larger Platform as a Service (PaaS) product. Yet, the focus soon shifted to fostering an open-source ecosystem, complemented by commercial support services.

In a significant rebranding move in 2013, 10gen Software adopted the name MongoDB Inc., aligning its corporate identity with its flagship product.

Main Features of MongoDB

MongoDB stands out in the database landscape, especially for enterprise-level projects and deployments, thanks to its array of robust features:

  • Ad-hoc Queries: MongoDB supports versatile querying options. This includes field and range queries, regular expression searches, and even user-defined JavaScript functions.
  • Indexing: It efficiently allows both primary and secondary indexing of fields within a document.
  • Replication: For high availability, MongoDB uses replica sets. In other words, it maintains two or more copies of data.
  • Load Balancing: The database achieves horizontal scaling through sharding. As mentioned in the intro, this means distributing chunks of data across multiple servers.
  • File Storage: With GridFS, MongoDB can double as a file system, managing large files efficiently.
  • Aggregation: MongoDB offers three methods for data aggregation. Those methods are: the aggregation pipeline, map-reduce functions, and single-purpose aggregation methods.
  • Server-side JavaScript Execution: This feature allows the use of JavaScript in queries, aggregation functions, and direct execution on the database.
  • Capped Collections maintain a fixed size, preserve insertion order, and function like a circular queue. They effectively manage space and enhance performance in specific scenarios.

Where Can MongoDB Be Deployed?

MongoDB provides a range of deployment options, catering to different operational needs and scales. The most straightforward option is on-premise deployment. You install and manage MongoDB directly on your data center servers. The advantage of this method is that it offers complete control over the database environment. Therefore, it can be ideal for organizations with specific regulatory or security requirements.

However, for handling large-scale data, the computational and storage demands often exceed what typical on-premise setups can offer. This is where cloud hosting becomes a significant advantage. Most opt to utilize a third-party cloud service like Amazon AWS, Microsoft Azure, or Google Cloud Platform. These platforms not only provide the necessary scalability but also offer robust infrastructure support.

Deploying MongoDB on a cloud platform has several benefits:

  • Scalability: Cloud platforms can dynamically scale resources to match your database’s growing data and traffic needs. This ensures consistent performance during peak loads.
  • High Availability: Cloud services offer built-in redundancy and failover capabilities. They minimize downtime and ensure continuous database availability.
  • Cost-Effectiveness: With cloud hosting, you typically pay only for the resources you use. Consequently, MongoDB can be more cost-effective than maintaining an on-premise infrastructure.
  • Global Reach: Cloud providers have data centers globally, allowing you to deploy your MongoDB database closer to your users. Globally located servers reduce latency and improve user experience.
  • Security and Compliance: Leading cloud providers offer advanced security features and compliance with various regulatory standards. They provide a secure environment for your data.
  • Managed Services: Many cloud platforms offer managed MongoDB services, where the cloud provider handles maintenance, updates, and backups.

While on-premise deployment of MongoDB offers control and security, most companies opt for cloud hosting because cloud hosting provides scalability, high availability, and efficiency.

MongoDB Services and Applications

MongoDB’s versatility and robustness as a NoSQL database open up endless possibilities for development across various domains. Some of the key applications and systems that can be efficiently built using MongoDB include:

  • Content management systems
  • Games
  • File sharing systems
  • Metadata projects
  • Logging applications
  • Geospatial data tools
  • Authorization and profiling applications
  • Product catalogs
  • Apps that integrate large amounts of data

Conclusion

When your current database infrastructure struggles to keep up with your company’s growth, it signals a need to reevaluate and possibly upgrade your data management strategy. Transitioning from traditional relational databases to more flexible and scalable NoSQL databases could be the key to addressing these challenges. Among the NoSQL options available, MongoDB stands out as a highly viable choice.

MongoDB isn’t just renowned for being free and open-source; it offers several compelling advantages for businesses looking to scale and evolve:

  • Scalability and Flexibility
  • Active Developer Community
  • Continuous Innovation
  • Compatibility with Modern Applications
  • Robust Support and Resources
  • Wide Range of Use Cases

In conclusion, migrating to MongoDB could be a strategic move if you’re encountering limitations with your current relational database setup. Its adaptability and strong community and corporate support make it a formidable choice for businesses aiming to thrive in a data-driven world.

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