5 FEATURES OF MongoDB LIKED BY WEB DEVELOPERS

What is MongoDB?

MongoDB is a database management platform that provides a NoSQL alternative to traditional databases such as SQL. While SQL is excellent when used with structured data, non-relational databases are very useful for developers that work with unstructured, distributed data. 

MongoDB is a helpful set of tools and capabilities that can manage text and documents, data storage, and fast transfer and retrieval. In fact, it was designed with accessibility in mind, even when you need to do complex querying. 

MongoDB acts as a database server where organizations can maintain several databases. It’s very efficient for developers to fetch and work with data.

Developers need tools that support large amounts of data to build modern web applications. MongoDB was created to address the need for software engineering and web development tools that meet the needs of today’s developers.

But what is MongoDB doing that makes it so well-suited to meeting these needs? Firstly, it uses a simple document model, so developers can learn and use it with ease while still offering users the ability to meet complex requirements. 

Each application that businesses work with has to be designed and built on a quality database that can maintain and support data transfer with other apps for a fast and secure user experience. Traditional (read: old-school) web applications depended on relational databases, but modern developers are leaning into alternative data stores like NoSQL with tools such as MongoDB. 

In short, MongoDB is great for web development. These databases help organizations design and build data-driven applications that look great and integrate seamlessly with other systems. They are built for high throughput, so developer platforms like MongoDB are superfast and come with automatic features to help maintain your applications.

Ease of Setup

First and foremost, MongoDB is very easy to install and deploy, and a developer can start writing code immediately for the application. As said, the installation of MongoDB is very simple whether it’s on Windows, Mac, or Linux. Even for Linux/Mac, one can download the tarball, extract it, configure the db/log path, and start it. Percona offers “Percona Server for MongoDB”, an enhanced, open source, and highly-scalable database that is a fully-compatible, drop-in replacement for MongoDB Community Edition. For more details on the installation of “Percona Server for MongoDB (PSMDB)” on various OS, please visit the installation section. One can also spin up MongoDB with Kubernetes, and Percona also has a Kubernetes Operator for Percona Server for MongoDB available.

Flexible Schema

One of the great features MongoDB has is a flexible schema. MongoDB can be a schemaless database. A developer won’t be stuck with a defined schema, i.e. we don’t need to define data-type in a collection before inserting the data or a field’s data type can be different across the documents in a collection.

Fault Tolerance

MongoDB has built-in Replication features that provide High Availability and redundancy. Since it has copies of data in multiple servers, it gives a layer of fault tolerance in case of loss of a database server. Having multiple copies of data in different regions increases the availability and data locality for reads with potential stale reading. It can also improve data locality for writes with zoned shards.

In the MongoDB Replica set, how many nodes can be unavailable and still have sufficient members to elect a new Primary is said to be the Fault Tolerance limit.

A correct fault tolerance configuration would be a mix of business consideration and budget. To achieve replication and fault tolerance of one, we would require a minimum of three nodes. So, if one node goes down, there will still be a majority of nodes available to elect a new Primary.

The below chart shows the number of required nodes to achieve fault tolerance.

Number of nodesMajority Required to Elect a New PrimaryFault Tolerance321431532642

Replica Sets can also increase the number of queries served to the application as clients can send read requests to secondaries of the replica set, i.e a client can set the readPreference to read from the secondary, “nearest”, or by a tag set. However, reading from secondary nodes comes with a tradeoff as well. Clients may see stale data.

Scalability

Scalability is one of the key features of MongoDB. It is built on a scale-out architecture which enables it to sustain a high volume of data and traffic.

In any database system, growth can be managed by two methods: vertical and horizontal scaling. Vertical scaling involves increasing the capacity of a single server like a more powerful CPU, increasing RAM, or extending disk space. Horizontal scaling involves dividing the dataset into multiple small machines without any code change to be made at the application level.

MongoDB supports sharding through Horizontal scaling. It is cost-effective, more data can be written or read back as necessary as you’re able to distribute the load across your shards. When there is an increase in dataset growth a new shard can be added at any time and MongoDB will automatically migrate the data.

In MongoDB, sharding happens at the collection level and each document is associated with a shard key which decides which shard the document should live on. The application doesn’t send requests to shards directly, it sends the requests to the MongoS [the Query router] and MongoS redirects the read/write request to the respective shards by cached metadata from the config servers.

Performance

Database performance varies with many factors like “Database design”, “application queries” and “load” etc. and MongoDB has the ability to handle large volumes of unstructured data because it allows users to query in a different way which is more appropriate to their workload. It is always faster to retrieve a related single document than to join data across multiple collections.

To get better performance, one needs to make sure that the working set fits in RAM as well. All data persists in hard-disk, except when using the in-memory storage engine, but during the query execution, it fetches the data from local RAM. It is also important to have the right indexes and enough RAM in place to get the advantage of MongoDB’s performance.

Conclusion

MongoDB is feature-rich, and an easy way to get started with NoSQL databases. It has a flexible data model, expressive easy to learn query syntax, automatic failover with replica sets, and is quite scalable. It also has good documentation which makes a developer’s life a lot easier.