CST363 - Week 6

SQL vs NoSQL

Most may believe that "NoSQL" is just a modern database experiment, but SQL-style databases were not the first around. In fact, NoSQL (meaning, non-SQL based) databases existed in the 1960s, whereas Oracle's SQL was not developed until the 1970s. However, the popularity of SQL databases cannot be ignored. The truth is that most databases are relational because it is a tried-and-true method of storing, retrieving, and updating large amounts of data. For small, simple data sets, any type of database should suffice. An example of when one may want to use a NoSQL database is when working with JSON documents, which are popular for web development due to their similarity to JavaScript objects and ability to handle high volumes of unstructured web data in real-time. 

Cassandra vs MongoDB

Two of the most popular NoSQL databases are Cassandra and MongoDB, both open-source systems developed at roughly the same time. One difference between them is how they handle queries. MongoDB uses JSON-type documents, but Cassandra has its own language called CQL (Cassandra Query Language), which is similar to SQL. MongoDB also uses a different architecture, requiring a single "master" node to control all "slave" nodes, while Cassandra has multiple master nodes per cluster, leading to greater uptime and write speeds. 

Choosing the right database can be tricky. In the case of MongoDB versus Cassandra, it seems like Cassandra is the better choice for high-volume systems that cannot go offline. It also provides a familiar user experience due to its similarity to SQL. However, MongoDB is supported by more programming languages, has built-in aggregation (Cassandra relies on 3rd party tools), and is more flexible in that it does not require use of a specific schema. Ultimately, each project has its own unique needs, and the project requirements will dictate which database to use.