Introduce
If you’re searching for NoSQL databases, you might come across Cassandra and MongoDB. Still, these two popular NoSQL choices have much less in common than expected.
What is the difference between Cassandra and MongoDB? In this tutorial, we’ll explain the similarities and differences between Cassandra and MongoDB.
Cassandra vs. MongoDB: Similarities
When comparing between two database systems, it is often inferred that they also have similarities. Although they do exist, these similarities are limited in the case of Cassandra and MongoDB.
NoSQL databases
What are the differences between Cassandra and MongoDB? On top of that, Cassandra and MongoDB are classified as NoSQL databases. NoSQL (not just SQL) is a popular alternative to traditional databases. Unlike relational databases as we know them, NoSQL can store large amounts of data without the need for logical categories or schemas.
Because traditional databases can’t handle large amounts of unstructured data in real time, NoSQL databases meet the challenge by scaling horizontally.
As a result, Cassandra was released in 2008 as one of these NoSQL databases. A year later, MongoDB was born.
Open-source software
Which is better Cassandra or MongoDB? Another common denominator between these two is that they are both free and open-source software. You can download, set up, and configure the database package for free.
Originally created by the developers at Facebook, Cassandra is now owned by the Apache project and is part of its open-source community. MongoDB, on the other hand, is one of the most popular database management systems in the world and has a strong community of MongoDB developers.
RDBMS and ACID cannot be replaced
Keep in mind that neither Cassandra nor MongoDB can replace traditional relational database management systems (RDBMS). If you need to store data in a structured format using rows and columns, stick to one of the many relational databases available.
Also, if you need an ACID-compliant database, NoSQL may not be the best solution. For database transactions that guarantee atomicity, consistency, isolation, and durability, it’s best to use a relational database, such as MySQL or PostgreSQL.
Cassandra vs. MongoDB: Differences
Data availability
What is the difference between Cassandra and MongoDB? One of the most significant differences between MongoDB and Cassandra is their strategy regarding data availability. This feature depends on the number of master-slaves in the cluster.
MongoDB has a master node that commands multiple slave nodes. If the master node fails, one of the slave nodes takes over its role. While the strategy of automatic failover does ensure recovery, it can take up to a minute to go from a server to a primary. During this time, the database is unable to respond to requests.
Cassandra, on the other hand, uses a different model. Instead of having only one masternode, it uses multiple masternodes within the cluster. With multiple masters present, don’t worry about any downtime. The redundancy model ensures high availability at all times.
Conclusion: If your application requires high availability and relies on an instant request response, then Cassandra is a more appropriate choice. However, make sure you have the server resources to facilitate this type of setup. If a delay of 30 to 40 seconds doesn’t impact your business, you don’t need to prioritize high availability and add additional infrastructure burden to your system.
Scalability
What are the differences between Cassandra and MongoDB? Scalability is a feature that is directly related to the clustering model. As a result, there is a significant difference in write scalability between Cassandra and MongoDB.
Only the master node can write and accept input. At the same time, the slave node is only used for reads. Correspondingly, since MongoDB has only one primary node, it is limited in terms of write scalability.
Having multiple primary nodes increases Cassandra’s write capacity. It allows this database to coordinate a large number of writes at the same time, all of which come from its master. Therefore, the more master nodes in the cluster, the better the write speed (scalability).
Conclusion: If you’re prioritizing write speed and scalability, consider Cassandra.
Data model
Which is better Cassandra or MongoDB? Now, let’s examine the data models of these two NoSQL databases.
MongoDB’s data model is divided into object-oriented and document-oriented. This means that it can represent any type of object structure that can have properties and even be nested at multiple levels.
When it comes to Cassandra, there’s a more traditional model. Cassandra has a table structure that uses rows and columns. Still, it’s more flexible than relational databases because you don’t need every row to have the same columns. At the time of creation, these columns are assigned one of the available Cassandra data types, ultimately relying more on the data structure.
Conclusion: If you need a rich data model, MongoDB may be the better solution. Its unstructured architecture gives you more flexibility and the opportunity to arrange objects in a given hierarchy.
Query language
Another differentiating factor is whether you need a database that supports a query language.
MongoDB uses queries structured as JSON fragments and doesn’t yet support any query language. If you or your team are used to SQL, this will be something to get used to. However, it is easy to manage.
Unlike MongoDB, Cassandra has its own query language called the Cassandra Query Language (CQL). Its syntax is similar to SQL, but there are still some limitations. Essentially, a database has a different way of storing and recovering data because it is non-relational.
Conclusion: If query language support is a must, Cassandra has you covered.
How are queries different?
What is the difference between Cassandra and MongoDB? In the example below, you can see how the query in MongoDB differs from the query used in Cassandra (when working in the demo employee table).
Select a record from the Employees table:
MongoDB
‘db.employee.find()’Cassandra
‘SELECT * FROM employee;’Insert a record into the Employees table:
MongoDB
‘db.employee.insert({ empid: '101', firstname: 'John', lastname: 'Doe', gender: 'M', status: 'A'})’Cassandra
‘INSERT INTO employee (empid, firstname, lastname, gender, status) VALUES('101', 'John', 'Doe', 'M', 'A');’To update a record in the Employees table:
database
'db.Employee.update({"empid" : 101}, {$set: { "firstname" : "James"}})'Cassandra
‘UPDATE employee SET firstname = ‘James' WHERE empid = '101';’How Cassandra differs from MongoDB: Supported programming languages
MongoDB： Actionscript、C、C#、C++、Clojure、ColdFusion、D、Dart、Delphi、Erlang、Go、Groovy、Haskell、Java、JavaScript、Lisp、Lua、MatLab、Perl、PHP、PowerShell、Prolog、Python、R、 Ruby、Scala、 Smalltalk
Cassandra： C#、C++、Clojure、Erlang、Go、Haskell、Java、JavaScript、Perl、PHP、Python、Ruby、Scala
Conclusion: The choice of programming language depends on your experience, project requirements (i.e., data volume and query type), and available frameworks. In general, both MongoDB and Cassandra support a wide range of programming languages. MongoDB is thought to work best with Node .js, but it’s hard to pick out a specific programming language.
Polymerization
Which is better Cassandra or MongoDB? The decision between MongoDB or Cassandra may also come down to whether or not you need a built-in aggregation framework.
MongoDB has a built-in aggregation framework. This feature allows it to retrieve data by leveraging ELT multi-level pipelines to convert documents into aggregate results. However, such a framework is only effective when dealing with small to medium-sized data traffic.
Cassandra does not have an aggregation framework and requires the use of external tools such as Hadoop and Spark.
Conclusion: The internal aggregation framework can only be found in MongoDB. If you’re looking forward to small to medium-sized data traffic and don’t want to involve external tools, then MongoDB has the upper hand in this regard.
Architecture
What is the difference between Cassandra and MongoDB? When it comes to architecture, you should decide whether you need a flexible database or a fixed database.
MongoDB is a database that doesn’t require schemas, which naturally makes it more adaptable to change. In its previous version, the default configuration did not enforce any schema at all. Today, you can decide if you want a pattern or not. This flexibility means that the database can input documents with different structures and interpret them once in the software.
Cassandra is a more stable database. It helps with static typing and requires columns to be categorized and defined beforehand.
Conclusion: If you need architectural flexibility, MongoDB may be a better fit for you. On the other hand, if you don’t expect too much bias in your data structure, Cassandra should be sufficient.
Secondary indexes
Which is better Cassandra or MongoDB? The quality of secondary indexes determines how efficiently you can access records in your database. These indexes are supported to varying degrees in MongoDB and Cassandra.
MongoDB has high-quality secondary indexes. Thanks to its flexible data model and secondary indexes, it can access any property of a stored object, even if it is nested.
Alternatively, Cassandra only provides cursor support for secondary indexes. Its queries are limited to single-column and equal comparisons.
Conclusion: The decision between the two depends on how you will query. If it’s mostly the primary index, Cassandra will do the job. If you need a flexible model with efficient secondary indexes, MongoDB would be the better solution.
Performance
What are the differences between Cassandra and MongoDB? There are a number of factors that can affect the performance of these two types of databases.
Mainly, database models (or schemas) have a big impact on the quality of performance, as some models are better suited to MongoDB and others may be better suited to Cassandra.
In addition, the load characteristics of the applications that your database needs to support also play a crucial role. If you’re expecting a lot of load input, Cassandra and its multiple masternodes will provide better results. Both MongoDB and Cassandra will show good performance with heavy workload outputs.
Finally, many believe that MongoDB has the upper hand in terms of consistency requirements. Still, this can vary from app to app. In addition, you can manually configure Cassandra to meet the consistency standards you set.
Conclusion
What is the difference between Cassandra and MongoDB? After reading this article, you should have a better understanding of the differences between Cassandra and MongoDB. Ultimately, the decision between these two NoSQL databases will depend on your needs and the model your application requires.
