What is the best SQL for MongoDB and Cassandra?
- This Cassandra vs. MongoDB comparison focuses on the two most significant NoSQL database products currently on the market: Cassandra and MongoDB.
- Although both of these NoSQL databases have a tendency to look similar, they differ from one another in a number of ways, so we'll talk about them for a while anyway.
Cassandra vs MongoDB: NoSQL DB Comparison
- Let's try to understand some of the similarities between these two NoSQL databases now that we have a better understanding of them both:
- These are both examples of NoSQL databases.
- None of these can be used in place of the standard RDBMS database types.
- These two databases do not both adhere to ACID standards.
- Because they skew more toward RDBMS database types, these two database types do not satisfy the concepts of consistency and normalization.
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- Larger companies like Google, Adobe, Forbes, eBay, Cisco, and many others use MongoDB.
What is Cassandra?
To understand Cassandra a little better, consider that it was first introduced in 2008 by a few Facebook developers and later made available as an Open Source project. The Apache Software Foundation is currently supporting it, and Apache is currently maintaining this project for any future improvements.
Third-party companies like Impetus, Datastax, and imagination provide support for this database. In companies like Facebook, Instagram, IBM, Reddit, and Netflix, Cassandra is used.
What is MongoDB?
A company called 10gen introduced MongoDB in 2009, just to give you some background information.
Later, 10gen changed its name to MongoDB Inc., which is now in charge of software development and also sells the enterprise version of the MongoDB database. With their excellent round-the-clock enterprise-grade support, MongoDB Inc. manages all the support.
Since they offer lifetime support, customers can use any version of MongoDB and can upgrade at any time with no interruption in service. Additionally, it gives them the chance to keep up with all the security updates that the company releases continuously.
Cassandra vs MongoDB: Difference between Cassandra and MongoDB
|
Features |
Cassandra |
MongoDB |
|
Modeling Data |
Rows and columns make up the more traditional data model used by Cassandra. In the case of Cassandra, data is organized, and each of these columns belongs to a particular type that is assigned at the time the table is created. MongoDB provides a richer data model than Cassandra, in comparison. |
The data model in MongoDB can be either data-oriented or object-oriented. Depending on the user domain, this model can also be represented using any data structure. If necessary, data can also be nested into a number of levels. |
|
Node Master |
One master node in the Cassandra cluster can be replaced by another if it goes down because there are multiple master nodes in the cluster. Due to the aforementioned, The cluster is not affected and is always accessible. In contrast to MongoDB, Cassandra offers a higher level of availability. |
MongoDB only has one master node in a cluster, which controls a number of slave nodes. A slave is chosen to take over as master if the master falls, and it takes about 20–30 seconds for the same. In this duration, the cluster won’t be able to accept any incoming requests. |
|
Secondary Indices |
The cursor support in Cassandra is restricted to a single column and equality comparison for the secondary index. |
Any property that is kept in the MongoDB database can be easily indexed. If your application needs flexibility in the data model and secondary indices, MongoDB is preferable to Cassandra. |
|
Scalability |
Cassandra is the best option for scalability because it can have multiple master nodes in a cluster. As it can have multiple master nodes in a cluster, Cassandra is more scalable than MongoDB. |
Only one master node, which acts as the only point of contact for incoming requests, is present at any given time in the MongoDB cluster. Hence, it is not ideal when we think about scalability. |
|
Query Language |
There is a proprietary query language for Cassandra named CQL, which is very similar to SQL. Cassandra has a user-friendly set of queries with CQL and is adaptable to the developers who have prior knowledge of SQL. |
There is no support for any query language for MongoDB. Queries are structured as JSON fragments in MongoDB. |
|
Aggregation |
Cassandra doesn’t have any built-in support for aggregation and heavily relies on tools like Hadoop or Apache Spark |
MongoDB has built-in support for aggregation which can be used to run an ETL pipeline in transforming the required data. MongoDB’s aggregation framework supports both small and medium data traffic. With the increased complexity, the framework gets tougher to debug as well. MongoDB is better in comparison with Cassandra, as it has a built-in aggregation framework. |
|
Schema |
Cassandra doesn’t provide the facility to alter schema but provides static typing. |
MongoDB provides the facility to alter schema for the Users |
|
Performance |
Cassandra performs better in applications with heavy data load as it can provide multiple master nodes in a cluster. |
MongoDB is not ideal for applications with heavy data load as it can’t scale with the performance. |
Conclusion
In this article comparing Cassandra and MongoDB, we have examined two NoSQL database variants that are currently on the market, thoroughly understood each of these NoSQL databases, and also seen the majority of similarities between these two database products. In addition, we have carefully examined the variations between these two database products and comprehended the areas where these products are most frequently used.