➜ Ease of use : CQL (Cassandra Query Language) is an alternative to SQL that Cassandra offers. ![]() Cassandra’s linear scalability assures rapid responsiveness. As a result of this horizontal scalability, you don’t have to shut down the database or make any substantial modifications. ➜ Scalability : As data and demands increase, you may quickly add extra hardware to meet those requirements. ➜ Performance : If there are many write requests, Cassandra can handle them quickly and efficiently without affecting the read requests. ➜ Data distribution flexibility : Cassandra may be set up to use several data centers if you like. ➜ Data storage flexibility : Cassandra allows you to store structured, semi-structured, and unstructured data. Thus, excellent availability is guaranteed. Hence, if any node fails, data can be easily retrieved from the remaining nodes. Each node handles the requests in the same way. ➜ Decentralization : Unlike other systems, Cassandra does not have a single point of failure. MongoDB has a “two-phase commit” feature that can be used to coordinate transactions across multiple database servers, but it is not as fully-featured as MySQL’s transactions. However, Cassandra has a feature called “lightweight transactions” that allows you to perform atomic updates on a single row. Cassandra and MongoDB do not support transactions in the same way as MySQL. ➜ Transactions : MySQL supports transactions, which allow you to group multiple SQL statements into a single unit of work that either succeeds or fails as a whole. MySQL has a robust and well-established query language called SQL, which is widely used and supported by many tools and libraries. MongoDB has a flexible query language that allows you to search for documents based on their contents. However, Cassandra is optimized for fast writes and efficient data retrieval, rather than complex querying. ➜ Querying : Cassandra has a powerful query language called CQL (Cassandra Query Language), which is similar to SQL. ![]() MySQL can also scale horizontally, but it may require more complex setup and maintenance. ➜ Scalability : Both Cassandra and MongoDB are designed to scale horizontally, which means they can handle large amounts of data and traffic by adding more machines to the database cluster. If you have structured data that fits well into a table-based model, MySQL might be a good choice. MySQL is a relational database, which means it stores data in tables with well-defined relationships between them. This can be beneficial for handling large amounts of unstructured data, or for storing data with complex relationships. ➜ Data model : Cassandra and MongoDB are both NoSQL databases, which means they use a non-relational data model. Here are some points to consider when deciding which DBMS to use: When choosing between Cassandra, MongoDB, and MySQL, it’s important to consider the specific requirements of your project and how each database management system (DBMS) meets those needs.
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