Previously we compared DynamoDB and MongoDB. MongoDB vs Cassandra is another frequently compared NoSQL database. Apache Cassandra is fully Free and Open Source Software which provides scalability. MongoDB is developed by MongoDB Inc, it has other options than just the MongoDB Open Source Software we commonly use. Apache Cassandra has scalability, linear performance, distributed architecture, faster read and writes capabilities. Cassandra uses a Query language called CQL (Cassandra Query language). CQL query language which is very similar to SQL.
Both of these databases read hot data set faster, both emphasize join-less data models, both provide indexes on documents or rows. But Apache Cassandra’s storage engine provides constant-time writes regardless of the size of data. Writes are problematic in MongoDB. MongoDB supports a rich, expressive object model which is object-oriented and is strikingly powerful. Cassandra offers traditional table structure with rows and columns. Hence data is more structured. MongoDB is a better choice for a rich data model. Cassandra does not have a built-in aggregation framework that is why Hadoop, Spark are used for that need. MongoDB has a built-in Aggregation framework to run an ETL pipeline which is great for medium jobs.
Cassandra is great for scaling, no-single-point-of-failure architecture, control over replication. For less than 100 nodes of the cluster, it is rationale to uses MongoDB. If cluster size is less then 1000 nodes, consistency and writing heavy operation needs then Cassandra is a good choice. For heavy read-heavy operation and high-reliability, Hbase is the big hammer. MongoDB is best for workloads with lots of highly unstructured data, lesser big project. Cassandra is more like MySQL and fits well with most of the big data software. MobgoDB clearly a great software for the simple works particular which uses a JSON format.