Top Features in MongoDB
MongoDB is one of the most admired and effortless NoSQL databases to set up. Developers want to spend time building the features for their application, and with MongoDB, developers can build the application quickly while utilizing well-supported infrastructure and high availability with automatic failover.
In this blog post, we will discuss the top features which MongoDB does better than anyone else.😃
Ease to 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.
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. A document from an student collection in MongoDB may look like:
{ "st_name" : "XYZ", "city" : "ID" }{ "st_name" : "XYZ", "city" : "NYC", "country" : "USA" }
Even if you have to change the structure of a document in a collection, you only need to update the document with a new structure. Consider a document of a phone collection below:
{"_id" : ObjectId("5f8d175127f5862e567f676c"),"model_name" : "iphone12","features" : {"5G_support" : true,"display" : "OLED with Ceramic Shield"}
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.
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.
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.
Sharding
When dealing with particularly large datasets, sharding — the process of splitting larger datasets across multiple distributed collections, or “shards” — helps the database distribute and better execute what might otherwise be problematic and cumbersome queries. Without sharding, scaling a growing web application with millions of daily users is nearly impossible.
Like replication via replication sets, sharding in MongoDB allows for much greater horizontal scalability. Horizontal scaling means that each shard in every cluster houses a portion of the dataset in question, essentially functioning as a separate database. The collection of distributed server shards forms a single, comprehensive database much better suited to handling the needs of a popular, growing application with zero downtime.
All operations in a sharding environment are handled through a lightweight process called mongos. Mongos can direct queries to the correct shard based on the shard key. Naturally, proper sharding also contributes significantly to better load balancing.
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.
