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Cassandra vs. MongoDB

by Brad Fein
Cassandra vs. MongoDB

NoSQL (short for “Not Only SQL”) databases are non-relational database systems that support unstructured data and this is the main feature that distinguishes them from SQL or relational databases. Just so we are on the same page, a database can be defined as a collection of information (data) that is organized in a system in such a way that it can be accessed, manipulated, and updated easily.

Apart from supporting unstructured data, NoSQL databases also feature the following.

  • There are different types of NoSQL databases depending on their data model. These include document databases, key-value stores, wide-column stores, and graph stores.
  • NoSQL databases are non-tabular. That is, they store data without a defined schema thus they will process both structured and unstructured data.
  • They use the distributed computing model that allows for the replication of data.
  • They scale faster, easily, and cost-effectively compared to the traditional database systems.

Cassandra and MongoDB are the two most popular NoSQL database systems. They have been used widely and grown to become the most preferred among others. For the professional, taking both the Cassandra and the MongoDB certification course offers a better ability to handle unstructured data.

What is Cassandra?

Cassandra is a wide-column store and among the most preferred NoSQL database systems. It was developed by Facebook developers in 2008 to perform an inbox search and soon became open-source. It is now managed by Apache Software Foundation which maintains constant updates on it hence Apache Cassandra. It is written in Java and uses CQL-Cassandra Query Language as its query language. Cassandra has been adopted by big names like Facebook, its originator, Twitter, Netflix, and eBay.

Cassandra is built to store and manage large volumes of unstructured data distributed across multiple commodity servers. It supports replication of data across clusters and data centers which makes it ideal for multiple data-center operations. Uniquely, in Cassandra, all data nodes are the same (It does not have Master-Slave architecture) which has worked to the advantage of its operations as all clients benefit from low latency access. Owing to this, Cassandra comes with three notable benefits.

  • It provides high availability of data and is thus tolerant to system faults
  • Consistent
  • It is highly and easily scalable

Features of Cassandra

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  • High linear scalability. Cassandra scales easily both horizontally by adding data centers and vertically by adding new nodes. Owing to this, Cassandra has among the fastest response times. The more the number of nodes the higher the throughput.
  • High availability and fault tolerance. Data is replicated across nodes and data centers. This makes it available such that hardware failure in any of the data centers will not affect operations.
  • supports replication. Data is replicated across multiple data centers.
  • Peer-to-peer (Distributed) architecture. All nodes are the same and they play the same roles unlike in the Master-Slave architecture.
  • CQL Query language. Cassandra uses CQL (Cassandra Query Language) especially developed to easily access this system.
  • Supports MapReduce with the Hadoop framework.

What is MongoDB

MongoDB is the most popular NoSQL database system. Developed in 2009, MongoDB is open-source and is also a document-based system that stores data in JSON-like documents. It came as a solution to handling web-based applications which required fast schema-less database management systems. MongoDB can store large volumes of data efficiently as it supports dynamic schema. MongoDB is written in C++ and uses MQL (MongoDB Query Language) as the query language.

While MongoDB is free, it has a paid enterprise version that the company sells to enterprises that need more customized services and support. This version runs on an enterprise’s infrastructure. Unlike Cassandra in which all nodes are the same, MongoDB supports a Master-Slave replication model.

MongoDB comes with the following advantages

  • It easily and highly scales horizontally with auto-sharding
  • Supports replication of data across clusters
  • High availability thus tolerant to system faults

Features of MongoDB

  • Automatic load balancing. Data is placed in shards hence enabling an automatic load balance of operations.
  • Replication. Master-slave performs reads and writes while a Slave can only perform reads. It copies and replicates data from the Master.
  • Duplication. MongoDB data is duplicated across multiple servers to keep the system operations tolerant to hardware failures.
  • Indexing. It can index any field in a document. 
  • Supports ad-hoc querying. Querying can be done based on field, range, and regular expressions.
  • Supports Map-reduce.

Cassandra vs. MongoDB

Cassandra and MongoDB are both popular. While they are both open-source, they differ in features and operations in many ways.

Release:

Cassandra was first released in 2008 by Facebook developers.

MongoDB was released in 2009 by MongoDB Inc.

Database structure:

Both Cassandra and MongoDB are NoSQL database systems.

However, Cassandra uses a table-like structure which consists of wide columns and rows that

Cassandra seems to resemble RDBMS in structure since they also use a tabular structure but Cassandra will handle unstructured data, unlike the traditional database systems. Cassandra also has the capacity to handle huge volumes of unstructured data.

MongoDB stores data in JSON-like documents in varied formats and can handle a wider array of data structures since it allows you to define and arrange objects in a hierarchical manner. 

Data availability:

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Cassandra agreeably excels in terms of data availability and speed at which data is written on the database more than MongoDB. This is perhaps the main distinguishing factor between the two.

Cassandra does not employ the Master-Slave nodes structure to mean that all nodes are available to perform writes and reads. It allows you to set-up several Masters such that when one node fails, the rest will be available to function. Hence in Cassandra, High Availability is easily achieved and maintained.

MongoDB, on the other hand, uses the Master-Slave structure that allows you to set up only one Master among the nodes in a cluster. Another Master node can only be set up in the event that the existing Master node fails. Having a single Master node to operate and automatically setting up another in case of failure achieves continuity but not as high availability as in Cassandra.

Implement language:

Cassandra is written in Java language.

MongoDB is written in the C++ language.

Query language:

Cassandra uses CQL (Cassandra Query Language) which resembles those of traditional RDBMSs.

MongoDB uses the MQL (MongoDB Query Language) to access data. It also supports other languages like JavaScript.

Best for:

Cassandra is best suited for situations that require elastic scaling. It is also good where rapid growth is expected as it can handle massive volumes of structured and unstructured data.

MongoDB, on the other hand, is best for situations with unpredictable unstructured data thanks to its flexible data structure. 

Overall,

Both MongoDB and Cassandra have their own special role to play in database management apart from replacing the RDBMS or ACID databases. 

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