Cassandra vs. MongoDB vs. Hbase: A Comparison of NoSQL Databases

NoSQL databases, unlike traditional SQL databases, are designed to handle large volumes of diverse data types without adhering to a strict schema, making them ideal for modern web-scale and real-time applications. The article compares three popular NoSQL databases: Cassandra, MongoDB, and HBase, each offering unique features and advantages. Cassandra, a wide column store database, excels in scalability and high availability, making it suitable for real-time applications but may suffer from inconsistency in replicas and lacks solid official documentation. MongoDB, a document store, provides flexibility through JSON-like documents and supports high availability with replica sets, though it faces challenges with memory usage and manual management tasks. HBase, also a wide column store, is built on Hadoop's HDFS and offers immediate consistency and failover support, but its master-slave architecture can be a single point of failure and requires complex integration with other systems. The choice between these databases depends on specific use cases, such as Cassandra's suitability for always-on applications, MongoDB's fit for real-time analytics, and HBase's strength in handling write-heavy applications.