In this tutorial, I will discuss what is a cluster in MongoDB. I will also discuss the different types of clusters.
In MongoDB, we use the word “cluster” to denote either a replica set or a sharded cluster. We will learn both these clusters in this tutorial detail in detail. Both these clusters have their own unique fundamentals which I will also cover.
So, let us get started with our tutorial!
What is Database Clustering?
Database clustering is the process of connecting multiple servers or instances to a single database. When a single server is unable to handle the volume of data or the number of requests, a data cluster is required.
An instance is a collection of memory and processes that interact with a database, which is a collection of physical files that store data.
Advantages of Database Clustering
So, many of you must be wondering why exactly would we do this. Why is a data cluster required for a database? Well, there are a lot of benefits tied to this process.
Let us discuss some of the benefits of database clustering for databases.
With database clustering, multiple computers collaborate to store data amongst themselves. This provides the benefit of data redundancy. Because all of the computers are synchronized, each node will have the same data as all of the other nodes.
We must avoid the types of repetitions (redundancies) that cause data ambiguity in a database. Because of the synchronization, the type of redundancy provided by clustering is guaranteed. In the event that a computer fails, we will have all of the data available to others.
The database does not include load balancing or scalability by default. It must be brought on a regular basis by clustering. It also depends on the configuration. Load balancing, in essence, distributes the workload among the various computers that comprise the cluster.
This means that more users can be supported, and if a large spike in traffic occurs for whatever reason, there is a better chance that it will be able to support the new traffic. One machine will not be able to handle all of the hits. This allows for seamless scaling as needed.
This is directly related to high availability. Without load balancing, a specific machine may become overworked, causing traffic to slow and eventually decrement to zero.
When you can access a database, it means it is accessible. The amount of time a database is regarded as available is referred to as its high availability. The amount of availability you require is heavily dependent on the number of operations you run on your database and how frequently you run any kind of analytics on your data.
We can obtain extremely high levels of availability with database clustering due to load balancing and having extra machines. Even if a server is shut down, the database will remain accessible.
Monitoring & Automation
Because monitoring and automation can be done easily with the software, a standard database can be used for this task. When a cluster is present, the advantage becomes more apparent. Typically, the advantage is that clustering allows for the automation of many database processes while also allowing for the creation of rules to alert potential issues. This eliminates the need to go back and manually check everything.
Automation is useful with a clustered database because it allows for notifications when a system is overloaded. A cluster, on the other hand, will have a designated machine that will serve as the database system for the entire cluster. This chosen machine can host scripts that run automatically for the entire database cluster and interact with all database nodes.
Types of Database Clusters in MongoDB
In MongoDB, you can have two different types of clusters for a database. it can be either replica sets or sharding. Let us understand what both mean and how they work, in brief.
What is a Replica Set in MongoDB?
A MongoDB replica set ensures replication by distributing data redundancy and high availability across multiple MongoDB servers.
If a MongoDB deployment failed to maintain a replica set, all data would be stored on a single server. If the main server crashes, all data is lost – but not if a replica set is activated. As a result, we can see the significance of having a replica set for a MongoDB deployment right away.
In addition to fault tolerance, replica sets can provide additional read operations capacity for the MongoDB cluster by redirecting clients to the additional servers, significantly reducing the load of the cluster.
Replica sets can also be useful for distributed applications because of the data locality they provide, allowing for faster and parallel read operations to occur on the replica sets rather than having to go through one main server.
What is a Sharded Cluster in MongoDB?
Sharding is the process of storing data records on multiple machines. This is MongoDB’s method of providing data scalability. In other words, it makes it easier to manage large amounts of data.
Let me try to make it even easier for you by providing an example. Assume you have a laptop capable of storing up to 250 GB of data. Over time, you accumulate a large number of files and notice that the performance of your laptop suffers. The more storage space you use, the worse your laptop performs.
Your application’s data is stored in the same way that commercial databases do. They are kept on machines. Sharding is required to maintain the performance of those machines while also allowing for faster responses from them to your app.
Because your application will grow over time, the machine cannot provide read and write throughputs. As a result, it solves the problem of horizontal scaling.
Throughputs are simply the amounts of data or units of information that enter or exit a system. It also refers to the amount of data that a system can process in a given amount of time.
So, this was all about clusters in MongoDB.