Difference Between MongoDB vs Cassandra
Let us study much more about MongoDB and Apache Cassandra in detail:
- Mongo DB has various licensing versions too. It was developed by MongoDB Inc. It first appeared and was released in the year 2009. MongoDB can also be used as a file system. Apache Cassandra was developed by Apache Software Foundation which was initially released in the year 2008. It supports cross-platform Operating System 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 is having elastic scalability, fast linear performance, easily distributed architecture, faster queries and transaction support, faster read and write capabilities. It was initially developed at Facebook for searching the messages in Inbox and was made open source later by Facebook. 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 major difference between MongoDB and Cassandra:
- Mongo DB supports ad-hoc queries, replication, indexing, file storage, load balancing, aggregation, transactions, collections, etc., whereas Apache Cassandra has main core components such as Node, data centers, memory tables, clusters, commit logs, etc.
- Mongo DB stores data in such a way that the data is stored in BSON files on disk whereas Apache Cassandra Node stores the data in it and its data centers consist of all the nodes.
- Mongo DB cluster contains different components such as shard, mongos and config servers to store metadata information and configuration settings details whereas Apache Cassandra cluster is distributed across different machines to handle failures and maintains the replicas to maintain the operations and transactions with high availability.
- Mongo DB works in the form of replicating all the instances in the entire server which is not done for single database level whereas Apache Cassandra has 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 to add a new field to every document in the entire collection which is adaptable whereas Apache Cassandra has the facility to add columns whenever or wherever wanted apart from the tradition relational based database systems.
- Mongo DB supports different types of data types along with some binary data and object types whereas Apache Cassandra deals with unstructured data and has a flexible schema to handle data read-write operations.
- Mongo DB architecture is designed in such a way that it balances the data automatically using its inbuilt feature in a shared cluster when the data grows as per requirement whereas Apache Cassandra is wide column based storage architecture based on the Big Data technologies and Dynamo DB database.
- Mongo DB is ranked in 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.
- Mongo DB supports multiple cross-platform operating systems such as Linux, Solaris, Windows, BSD, OS X, etc. whereas Apache Cassandra supports Linux, OS X, Windows, BSD Operating Systems.
MongoDB and Cassandra Comparison Table
The primary comparison between MongoDB and Cassandra are discussed below:
|Basis of Comparison between MongoDB vs Cassandra||
|License||Open Source No SQL database licensed under Apache License||Open Source No SQL database developed by Apache Open Source Projects|
|Environment||Developed by MongoDB Inc. and supports cross-platform systems||Provided by Apache projects and useful for distributed environments|
|Performance||Provides faster query execution performance due to a simple schema||Provides high scalable and linear performance|
|Scalability||Writing scalability is limited in MongoDB||High scalability.|
|Pricing||Open Source and depends on the implementation and has different licensed versions too||Open Source and depends on the implementation|
|Speed||Not faster compared to Cassandra in terms of read operations||Faster for queries of smaller scripts|
|Query Speed||Reduces network speed while multi-query execution||Multi-Query execution capacity|
|Data Integration||Fast and Flexible with different applications and tools such as Big Data.||Fast and Flexible with different tools|
|Data Format||BSON and JSON data formats.||No SQL, JSON data formats.|
|Ease of Use||Easier to write scripts||Easier to write scripts and queries.|
Mongo DB is No SQL and document-oriented database and Apache Cassandra is also a No SQL based database system, where Elasticsearch is clearly a winner in terms of latest object-oriented or No SQL databases is based on Lucene developed by Apache which is a good index based search engine. In terms of performance scalability and the features, Apache Cassandra can be considered the best database in the case of large amounts of data to be handled and in terms of query execution speed and optimization.
The advantages of MongoDB are that the complex data can be easily be modeled because of the JSON format support provided. This gives much popularity for the Mongo DB compared to the Cassandra. Both MongoDB vs Cassandra Performance the databases have their greater advantages depending on the requirements and the amount of data about to be handled in the application decides the choice to be made.
This has been a guide to the top difference between MongoDB vs Cassandra. Here we also discuss the MongoDB vs Cassandra key differences along with infographics and comparison table. You may also have a look at the following articles MongoDB vs Cassandra to learn more –