Cassandra vs. MongoDB

Introduction

Mobile phones, wireless networks, and, most notably, the Internet have all been gifts to humanity courtesy of the rapid development of technology. The Internet is teeming with vast amounts of information, all of which can be accessed with the press of a button. The immensity of the amounts of data necessitates its digital storage in a database, which is managed by a database management system (DBMS). These kinds of databases include Cassandra and MongoDB, for example.

If you have been looking at NoSQL databases, you have undoubtedly heard of Cassandra and MongoDB. However, despite their widespread use, these two NoSQL databases have much less in common than one would think.

It is common practice to infer the existence of shared commonalities between two database management systems when performing a comparison between them. Even though they are there, the similarities between Cassandra and MongoDB are, on the whole, relatively little.

The main difference between Cassandra and MongoDB is that the former works on a hybrid data model consisting of tabular structure and key-value and uses a "peer-to-peer" architecture model. In contrast, the latter's data model is an object- and document-oriented and uses a "master-slave" model. Cassandra works on a hybrid data model that consists of tabular structure and key-value, and it uses a "peer-to

The Cassandra database uses a "peer-to-peer" architectural approach, an open-source NoSQL database. Cassandra has not just one controller node but numerous controller nodes within a cluster because of this characteristic. As a result, even if one controller node goes down, other controller nodes can take over and guarantee that the database always answers all queries. In addition, only the controller node can write and receive input; however, since Cassandra employs the cluster architecture, numerous controller nodes can write and accept information simultaneously.

Cassandra's high data availability and flexible scalability are both achieved via the use of this paradigm. Cassandra is a NoSQL database management system that is open-source and free to use. It uses general column stores and is distributed. The Apache Software Foundation created it, and the first version was made available in July of 2008. Cassandra was developed to manage massive volumes of data over a distributed network of commodity computers, delivering high availability while eliminating the possibility of a single point of failure.

The "master-slave" paradigm is the foundation of MongoDB, another open-source NoSQL database like MySQL and MariaDB. Because of this, if the controller node is unable to operate, the role of the controller node may be taken over by an agent node. However, the transition to the new master node might take a few minutes, and during this time, the database will not be able to reply to queries. Because of this, the availability of the data is affected. In addition, the scalability of MongoDB is restricted because only the master node can write and receive inputs, while the slave nodes are useful only for reading the database.

MongoDB is a document-oriented and nonrelational (also known as NoSQL) database application that works across several platforms. It is a document database that is available for anybody to use and holds information in the form of key-value pairs. MongoDB is a database management system that was first made available to the public on February 11, 2009, and was created by MongoDB Inc. It is composed of code written in the languages C++, Go, JavaScript, and Python. MongoDB excels in all three categories of performance: speed, availability, and scalability.

Difference Between Cassandra and MongoDB in Tabular Form

Parameter of Comparison	Cassandra	MongoDB
Data Model	It is a cross between a key-value database and a table structure, which makes use of rows and columns.	It has a data model that is both object-oriented and document-oriented.
Programming Language Support	C++, Python, Java, JavaScript,.Net, Ruby, PHP, Scala, Perl, C#, Clojure, Go, Erlang, and Haskell are among the programming languages that are supported.	C, C++, C#, Clojure, ColdFusion, Dart, Delphi, Ruby, Python, Scala, JavaScript, Java, Erlang, Go, Groovy, Haskell, PHP, Perl, Lisp, Lua, MatLab, PowerShell, Prolong, and Smalltalk are among the programming languages that are supported.
Aggregation Framework	Does not have its own aggregation architecture and instead on on support from third-party technologies like as Hadoop, Apache Spark, and others.	It contains a foundation for aggregation that is already built into it.
Schema	Due to the fact that it has a flexible schema, it is not necessary for each row to have the same amount of columns within the same column family.	The most recent version of MongoDB allows users to choose whether or not they wish to use schema, which makes the database far more adaptable.
Query Language Support	Cassandra's own query language is called Cassandra Query Language, or CQL for short.	Although it does not yet have a query language, it makes use of the JSON data format.

What is Cassandra ?

Cassandra was first launched in 2008 and was built by Facebook specifically for inbox search. In 2009, it was accepted into the Apache software foundation as a new project and was given the name Apache Cassandra.

Data is stored in a Cassandra database, which is a NoSQL database. This database uses a fundamental data structure consisting of column families, rows, columns, and keyspace. Because Cassandra has a flexible schema, rows within the same column family might have a varying number of columns even if they belong to the same family.

On the other hand, Cassandra makes use of a distinct model. It employs many controller nodes inside a cluster rather than having a single node that serves as the master. There is no chance of any downtime occurring since there are numerous masters present. The redundant approach guarantees a consistently high level of availability at all times.

Cassandra's capacity for writing is improved when numerous controller nodes are available. It makes it possible for this database to coordinate many write operations simultaneously, all of which originate from its masters. Therefore, the number of controller nodes in a cluster directly correlates to the write speed (scalability).

Cassandra's distributed database system contains a cluster of nodes, and each node performs the same duties and processes the same kinds of requests. In place of the traditional "master-slave" architecture, Cassandra implements the concept of a "coordinator node." This indicates that when a client makes a request, the node that receives the request becomes the coordinator for that particular request. This node is responsible for coordinating the exchange of responses between the node containing the information to the client's request and the node responsible for sending the result to the client.

Several well-known websites, including Netflix, Twitter, Viacom Hosting, Walmart Labs, Spotify, Reddit, Instagram, and Facebook, are among Cassandra's customers.

What is MongoDB?

In 2007, 10gen, now known as MongoDB, Inc., created MongoDB, a NoSQL database, to resolve challenges about scalability.

Since it is a document-oriented database, the fundamental structure for storing data is in the form of documents. This is how the data is organized. In this context, the fundamental structure used for storing a single item of data is referred to as a document. Because there is no schema, the documents that make up a collection all have distinctive formats and contents, although sharing the same name.

Only the controller node can write and read input from other nodes. In the interim, read operations are only performed on the agent nodes. Consequently, MongoDB's writing scalability is restricted because it only has a single controller node.

MongoDB is organized by a solitary master that oversees numerous agent nodes. If the controller node becomes unavailable, one of the agent nodes will assume control of the network. It may take up to a minute for the enslaved person to become the master when using an automated failover technique, even though this method does guarantee recovery. During this period, the database will not be able to process any requests.

Because JSON is used as the query language for the documents stored in MongoDB, the structure of this database may also allow object-oriented programming.

As a consequence of the fact that MongoDB is built on a master-slave paradigm, the database will become inaccessible for a few minutes if the master node fails to perform its duties. MongoDB addresses this issue by implementing a replica set, which includes a master node, also known as the main node, as well as all of the subordinate nodes. Because of this, the master node becomes the receiver of all of the requests that are made by the client, and it also keeps all of the changes in the operation log that it maintains. To ensure that all of the data is accurate and up to date, the slave nodes read the operation log from the primary node and apply any necessary updates to their copies of the data.

MongoDB makes use of a communication mechanism known as "heartbeat" and "elections" if the main node fails. The members of the replica set communicate with each other by sending heartbeats at regular intervals of two seconds. If a member does not respond to a heartbeat within ten seconds, it is assumed that the member has died, and the secondary nodes are alerted of this fact. After this, the replica set organizes an election and casts its votes to choose the secondary node that will succeed the original primary node as the new primary node.

The election will be won by the secondary node that received the most votes. If two or more secondary nodes have an equal number of votes for the main node, there is a third kind of node that is referred to as the Arbiter. Some of the most notable companies in the world utilize MongoDB, including Abode, Google, Forbes, Facebook, eBay, BOSH, and Cisco.

Main Differences Between Cassandra and MongoDB in Points

Data is stored in a tabular format by Cassandra, but MongoDB employs an objective, data-oriented paradigm.
A cluster of nodes is used by Cassandra to provide high data availability. MongoDB, on the other hand, only has one master node, which limits the availability of its data.
Cassandra offers flexible scaling because of the equality of all ring nodes. MongoDB, in comparison, only has one master node that stores all of the data, therefore it cannot scale up or down easily.
Cassandra depends on third-party tools since it lacks an internal aggregation framework. The internal aggregation framework of MongoDB, on the other hand, is best suited for small and medium-sized data flow.
In contrast to Cassandra, which enables ad-hoc queries, file storage, collections, replication, and transactions, MongoDB supports memory tables, commit logs, clusters, data centers, and nodes.
Cassandra has its query language called CQL, unlike MongoDB (Cassandra Query Language). Although it has significant restrictions, its syntax is close to SQL. Due to the database's non-relational nature, it essentially has a distinct method for storing and recovering data.
Both object-oriented and document-oriented data models are used in MongoDB. This implies that it may represent any kind of object structure, even those with attributes or several layers of nesting. There is a more conventional framework for Cassandra. Rows and columns are used to create tables in Cassandra. It is nevertheless more adaptable than relational databases since not all rows must have the same set of columns. These columns are given one of the possible Cassandra data types when they are created, which ultimately relies more on the data structure.
Only the master node can write and receive input. The slave nodes are only used for reads in the interim. As a result, MongoDB's writing scalability is constrained since it only has one master node. Cassandra's writing power is increased by having several master nodes. It enables this database to manage several simultaneous writes coming from its masters. Consequently, write performance increases with the number of master nodes in a cluster (scalability).

Conclusion

Cassandra and MongoDB are examples of NoSQL database management systems; nevertheless, there are several critical distinctions between the two. Cassandra appears to be more critical when working with transactional data, although MongoDB is more effective for conducting real-time analytics.

References

Introduction
Cassandra vs. MongoDB
Difference Between Cassandra and MongoDB in Tabular Form
What is Cassandra ?
What is MongoDB?
Main Differences Between Cassandra and MongoDB in Points
Conclusion
References

Difference Between Cassandra and MongoDB

Introduction