The difference between MongoDB vs. Apache Cassandra
Let’s take a closer look at MongoDB and Apache Cassandra:
- Mongo DB also has different licensing versions. It was developed by MongoDB Inc. It first appeared and was released in 2009. MongoDB can also be used as a file system. Apache Cassandra was developed by the Apache Software Foundation, which was released in 2008. It supports a cross-platform operating system. The Cassandra database provides high availability and no single point of failure.
- It also benefits in the case of Scalability. Compared to relational databases, NoSQL databases support powerful queries and transactions by following ACID properties (atomicity, consistency, isolation and durability).
- Apache Cassandra has flexible scalability, fast linear performance, an easily distributed architecture, faster queries and transaction support, and faster read and write capabilities. It was originally developed by Facebook for searching messages in the inbox, and later became open source by Facebook. Cassandra has a query language called CQL, which is Cassandra’s query language.
Here are the top 6 differences between MongoDB vs. Apache Cassandra
Key differences between MongoDB vs. Apache Cassandra
And MongoDB vs Cassandra performance is a popular choice on the market; Let’s discuss some key differences between MongoDB and Cassandra:
- Mongo DB supports ad-hoc queries, replication, indexing, file storage, load balancing, aggregation, transactions, collections, etc. etc., whereas Apache Cassandra has core core components such as Node, data centers, memory tables, clusters, commit logs, etc.
- Mongo DB stores data in such a way that data is stored in BSON files on disk, whereas Apache Cassandra Node stores data in it, and its data centers consist of all nodes.
- The Mongo DB cluster contains various components such as shard, mongos, and configuration servers to store metadata and configuration parameter information, while the Apache Cassandra cluster is distributed across different machines to handle failures and maintains replicas to ensure high availability of transactions and transactions.
- Mongo DB works in the form of replication of all instances across the server, which is not performed for a single database layer, whereas Apache Cassandra has a replication factor that determines the number of data copies on different machines to get multiple copies of data for fault tolerance. and high availability.
- Mongo DB can make it easy to add a new field to every document in the entire collection that can be adapted, while Apache Cassandra has the ability to add columns anytime and anywhere other than traditional relational database systems.
- Mongo DB supports a variety of data types along with some binary data and object types, while Apache Cassandra works with unstructured data and has a flexible scheme for handling read-write data operations.
- The Mongo DB architecture is designed so that it automatically balances data using an embedded function in a shared cluster when data grows as required, whereas Apache Cassandra is a wide-column storage architecture based on big data technologies and the Dynamo DB database.
- Mongo DB is rated in the top 5 in terms of engine ratings, while Apache Cassandra scores less in terms of database engine ratings in terms of popularity and trends.
- Mongo DB was released in 2009, while Apache Cassandra was released in February 2008.
- Mongo DB supports several cross-platform operating systems such as Linux, Solaris, Windows, BSD, OS X, etc. etc., while Apache Cassandra supports Linux, OS X, Windows, BSD Operating Systems.
Conclusion – MongoDB vs. Apache Cassandra
Mongo DB is a non SQL and document-based database, and Apache Cassandra is also a non SQL based database system, where Elasticsearch clearly wins in terms of the latest object-oriented databases, or the No SQL database is based on Lucene, developed by Apache, which is a good index-based search engine. In terms of scalable performance and features, Apache Cassandra can be considered the best database when dealing with large amounts of data, as well as in terms of speed and optimization of query execution.
The advantages of MongoDB are that complex data can be easily modeled due to the JSON format support provided. This gives MongoDB greater popularity compared to Cassandra. Both MongoDB and Cassandra Performance databases have their own great advantages depending on the requirements, and the amount of data to be handled in the application decides which choice is made.
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