Both Cassandra and hbase are designed to manage very large datasets.

In Java mall development, we all know that Cassandra and hbase are nosql databases. In general, this means that you cannot use the SQL database. However, Cassandra uses cql (Cassandra query language), and its syntax has obvious traces of imitating SQL.
In JSP mall development, both are designed to manage very large datasets. The hbase file claims that an hbase database can have hundreds of millions or even billions of rows. In addition, users are recommended to continue using relational databases. Both are distributed databases, not only for data storage, but also for data access. The client can be connected to any node in the cluster and access any data. Both claim to have linear scalability. Want to manage twice the size of data? You only need to double the number of nodes in the cluster.
Both use replication to prevent data loss caused by cluster node faults. The Rows written to the database are the responsibility of a single cluster node (the ing between rows and nodes depends on the partition mode used by the user ). The data is mirrored to other cluster members that are called redundant nodes (the number of replication factors that can be configured by the user is displayed ). If the primary node fails, the data can still be read from other redundant nodes.
Both are called columnar databases. Since their names sound like relational databases, users need to adjust their minds in contact, which leads to confusion in users' cognition of them. Most confusing is that data is initially arranged by rows on the surface, and the table's primary key is the row key. However, unlike a relational database, in a columnar database, no two rows need the same columns. As mentioned above, after a table is created, you can quickly add columns to the row. In fact, you can add many columns to a row. Although the maximum limit is difficult to accurately calculate, it is almost impossible for users to reach this limit, even if they add a large number of columns.