MongoDB is a NoSQL database meaning it doesn’t force data to be stored according to a rigid schema. In other words, data isn’t stored in tables, like relational, SQL-based databases. Instead of using rows and columns to store structured data like SQL databases, MongoDB databases store their data in collections and documents.
MongoDB data records are stored in BSON (Binary JavaScript Object Notation) format. Applications can then retrieve document data records from a MongoDB via a JSON (JavaScript Object Notation) format. Using BSON for data storage means the MongoDB can accommodate a wide variety of data types.
Is MongoDB NoSQL?
Yes, MongoDB is a NoSQL (or non-relational) database technology. In practice, this means you can use MongoDB to store both structured, semi-structured and unstructured data. With MongoDB you can store very simple data, like text files, alongside more complex data, like videos.
What Is MongoDB Used For?
MongoDB can handle large amounts of data quickly and was built to be used for both application development and application scaling. Here are six key reasons why you might deploy a MongoDB database.
1. Document-Oriented
MongoDB is a NoSQL database technology. It stores its data in JSON format rather a relational format that you’d find in SQL databases. This makes MongoDB flexible because data can be stored in a hierarchical format within the JSON document, thereby making it easy and fast to retrieve records.
2. Flexible Querying
MongoDB supports ad hoc querying by the fields within its document data records. You can also query by regular expression and range queries. This makes querying and finding data within a MongoDB database fairly straightforward for most use cases.
3. Flexible Indexing
You can index any field in a document data record. You can then use those indexes to improve the performance of searches within MongoDB to provide even more flexibility.
4. High Speed
MongoDB is known to perform fast even when dealing with huge amounts of data. This is a major benefit to applications that need to quickly search for a piece of data and then display that data output to an end user.
5. Application Language Agnostic
MongoDB provides drivers to store and retrieve data from applications developed in a range of different languages such as Node.js, Python, Java, C# and more. This flexibility makes MongoDB a versatile tool across a range of applications, regardless of their development language.
6. Sharding
MongoDB instances can scale horizontally through a process called sharding. Sharding refers to the process wherein data from a large data set is divided and automatically distributed across multiple servers. If one server can’t handle a data load, it can be divided and distributed to other servers without any interruption to data processing. This is important for applications that rely on a high availability of data.
Benefits of MongoDB
MongoDB is a great choice to support applications that need to handle various types of data (structured, semi-structured and unstructured) as well as needing to utilize large amounts of data. MongoDB works well when an application needs high availability of data, flexibility of data storage, ability to scale-out quickly or the ability to support real-time analytics and big data needs.
MongoDB can have a range of use cases when a NoSQL, high speed, scaled database solution is appropriate. Two more prominent examples include:
- Real-Time Analytics: MongoDB’s NoSQL, schema-less structure makes it a good choice for real-time analytics and fast processing of big data. Its schema-less structure means various types of structured and unstructured data can be stored and retrieved for single-view across multiple types of data and data sources. Also, MongoDB’s built in sharding allows it to scale data across multiple servers ensuring uptime and quick access to data by leveraging multiple servers.
- Content Management: MongoDB’s non-structured document-model is excellent for content storage and management, thereby allowing users to store a variety of content in a single MongoDB instance — from the simple to the complex. This might include text, images, metadata and video. MongoDB’s storage flexibility makes it a great choice for e-commerce sites, online publications and online content management systems that need the flexibility to store various formats of data.
Disadvantages of MongoDB
Broadly speaking the disadvantages of MongDB are the same that you’ll have with any NoSQL database platform. Here are some disadvantages to consider with MongoDB and other NoSQL technologies:
- ACID: The most cited drawback of NoSQL databases is that they don’t support ACID (atomicity, consistency, isolation and durability). This raises issues of security and querying isolation. That said, MongoDB has started to introduce tools in its most recent releases (release 4.0+) that begin to address challenges here.
- Less mature: MongoDB and other NoSQL database platforms are less mature, so that means tools and support are also less mature than you’d get from an SQL database platform.
- Compatibility with SQL databases: A lot of NoSQL databases like MongoDB have their own instructions and characteristics that can mean compatibility issues with SQL databases.
- Standardization: NoSQL databases don’t have the same level of standardization across platforms that relational databases offer, due again to the platforms’ relative novelty.
- Scale-out: MongoDB has scale-out abilities via its replica sets, but the scale-out performance may be limited compared to what relational databases platforms can produce.
SQL-based databases should be your tool of choice when your data schema is predictable and stable or when you don’t need unstructured data. Moreover, SQL-based databases are preferable when you need a high-transaction rate, security-enforced table relationships or when the data isn’t likely to change.
