Updated March 20, 2023
Difference Between MongoDB vs Cassandra
Let us study much more about MongoDB and Apache Cassandra in detail:
- Various licensing versions of MongoDB exist. MongoDB Inc. developed it and released it in 2009. Additionally, MongoDB can function as a file system. The Apache Software Foundation developed Apache Cassandra, first released in 2008. It supports cross-platform Operating Systems Cassandra database provides high availability and zero single points of failure.
- It also wins in the case of Scalability. Compared to relational databases, NoSQL databases support powerful queries and transactions by following ACID (Atomicity, Consistency, Isolation, and Durability) properties.
- Apache Cassandra has elastic Scalability, fast linear performance, easily distributed architecture, faster queries and transaction support, and faster read and write capabilities. Facebook initially developed it for searching messages in the Inbox and later made it open Source. Cassandra has a Query language called CQL which is Cassandra Query language.
Head To Head Comparison Between MongoDB and Cassandra (Infographics)
Below is the top 10 difference between MongoDB and Cassandra:
Key differences between MongoDB and Cassandra
Let us discuss some of the significant differences between MongoDB and Cassandra:
- MongoDB supports ad-hoc queries, replication, indexing, file storage, load balancing, aggregation, transactions, collections, etc. In contrast, Apache Cassandra has core components such as Node, data centers, memory tables, clusters, commit logs, etc.
- MongoDB stores data in such a way that it is stored in BSON files on disk, whereas Apache Cassandra Node keeps the data in it, and its data centers consist of all the nodes.
- MongoDB cluster contains different components such as shard, mongos, and config servers to store metadata information and configuration settings details. In contrast, the Apache Cassandra cluster is distributed across other machines to handle failures and maintains the replicas to sustain high-availability operations and transactions.
- MongoDB works by replicating all the instances in the entire server, which is not done for a single database level. In contrast, Apache Cassandra has a replication factor that defines the number of copies of data across different machines to receive multiple copies of data to maintain fault tolerance and high availability.
- Mongo DB can facilitate adding a new field to every document in the entire collection, which is adaptable. In contrast, Apache Cassandra can add columns whenever or wherever wanted, apart from the traditional relational-based database systems.
- MongoDB supports different types of data types, binary data, and object types. In contrast, Apache Cassandra deals with unstructured data and has a flexible schema for read-write data operations.
- MongoDB architecture is designed to balance the data automatically using its built-in feature in a shared cluster when the data grows as required. In contrast, Apache Cassandra is comprehensive column-based storage architecture based on Big Data technologies and the DynamoDB database.
- MongoDB is ranked in the top 5 in terms of engine ranking, whereas Apache Cassandra scored less in terms of DB engine ranking in terms of popularity and trending.
- Mongo DB was released in 2009, whereas Apache Cassandra was initially released in February 2008.
- MongoDB supports multiple cross-platform operating systems such as Linux, Solaris, Windows, BSD, OS X, etc., whereas Apache Cassandra supports Linux, OS X, Windows, and BSD Operating Systems.
MongoDB vs Cassandra Comparison Table
The primary comparison between MongoDB and Cassandra is discussed below:
|Basis of Comparison
|Open Source NoSQL database licensed under Apache License
|Open Source NoSQL database developed by Apache Open Source Projects
|Developed by MongoDB Inc. and supports cross-platform systems
|Provided by Apache projects and useful for distributed environments
|Provides faster query execution performance due to a simple schema
|Provides high scalable and linear performance
|Writing Scalability is limited in MongoDB
|Open Source depends on the implementation and has different licensed versions too.
|Open Source and depends on the implementation
|Not faster compared to Cassandra in terms of read operations
|Faster for queries of smaller scripts
|Reduces network speed while multi-query execution
|Multi-Query execution capacity
|Fast and Flexible with different applications and tools such as Big Data.
|Fast and Flexible with different tools
|BSON and JSON data formats.
|No SQL, JSON data formats.
|Ease of Use
|Easier to write scripts
|Easier to write scripts and queries.
MongoDB and Apache Cassandra are NoSQL and document-oriented database systems, while Elasticsearch, based on Lucene developed by Apache, is a leading object-oriented or NoSQL database. Elasticsearch is known for its excellent index-based search engine. Apache Cassandra is the best database for handling large amounts of data and optimizing query execution speed and Scalability.
The advantages of MongoDB are that the complex data can be easily modeled because of the JSON format support provided. This gives much popularity for the Mongo DB compared to Cassandra. The choice between MongoDB and Cassandra Performance databases depends on the requirements and the amount of data that the application needs to handle.
Frequently Asked Questions (FAQs)
Q1 What is Cassandra DB used for?
Cassandra DB handles large amounts of structured, semi-structured, and unstructured data across multiple commodity servers while providing high availability and fault tolerance. It is commonly used for use cases such as real-time data analytics, IoT, messaging systems, e-commerce, and more.
Q2 Is MongoDB faster than Cassandra?
It is difficult to say definitively which is faster between MongoDB and Cassandra as it depends on various factors such as the use case, data size, and hardware configuration. However, Cassandra is generally better suited for write-heavy workloads and large-scale distributed systems. At the same time, MongoDB is better suited for read-heavy workloads and applications that require flexible data models.
Q3 What is the major drawback of cassandra and MongoDB?
- One potential drawback of Cassandra is that it requires careful data modeling and may not be the best fit for use cases with complex queries.
- One potential drawback of MongoDB is that it can be memory-intensive and perform poorly as other databases for use cases with frequent updates.
This has been a guide to the top difference between MongoDB vs Cassandra. Here we also discuss the MongoDB vs Cassandra key differences, infographics, and a comparison table. You may also have a look at the following articles to learn more –