Data Modeling in Cassandra (IT315)

Data Modeling is an important part of database design.

Traditional relational databases rely on denormalized tables with foreign keys and support table joins.

In Cassandra, data modeling follows a query-driven approach, optimized for specific data access patterns.

Cassandra is a traditional relational database.

Cassandra's data modeling is based on data access patterns and application queries.

In Cassandra, queries are designed to access multiple tables for faster data retrieval.

Denormalization and data duplication are key elements for improving performance in Cassandra.

Which of these are not components of Cassandra data model?

Keyspaces in Cassandra serve as data containers and are similar to schemas in traditional databases.

Replication in Cassandra is configured and applied at the column level.

In Cassandra, columns can have different data types, including text, float, double, and counter

Tables in Cassandra are created inside keyspaces, and they are designed to support denormalization for efficient querying.

Data duplication is not recommended in Cassandra as it increases storage costs and can lead to data inconsistency.

Every table in Cassandra must have a primary key for unique row identification.

Cassandra operates within a cluster of interconnected machines, but each cluster has only one node for performance optimization.

In Cassandra, data is arranged and distributed in a ring pattern, ensuring a circular flow of data across nodes.

Cassandra uses a secondary key for unique row identification, which comprises a partition key and optional clustering columns.

The partition key in Cassandra determines the specific data access pattern and defines the way data is distributed among nodes.

Clustering columns are used to arrange data within each partition, ensuring a sorted and consistent order of rows.

In Cassandra, a partition is a set of rows with unique data points and does not share the same partition key.

Partitions in Cassandra represent a physical unit of access, ensuring that data is retrieved from a single location for fast access.

Cassandra optimizes queries by arranging rows within partitions based on the values of clustering columns.

One of Cassandra's performance optimizations involves having as many partitions as possible to ensure faster read and write operations.

Which rule of Cassandra data modeling states that it is beneficial to have as few partitions as possible for faster read performance?

The rule "Maximize Data Duplications" ensures that Cassandra uses data redundancy within the clusters for high availability and to prevent data loss.

The rule "Spread Data Evenly" emphasizes the balanced distribution of data across all cluster nodes for performance optimization and resilience.

The rule "Create Tables Based on Queries" recommends designing tables based on the specific queries that will be used to access them.

Which of these is NOT a common type of database relationship?

A one-to-one relationship means that there is a direct and unique correspondence between two entities, with each entity linked to a single instance of the other entity.

A one-to-many relationship means that a single instance of one entity can be associated with multiple instances of another entity.

A many-to-many relationship represents a scenario where multiple instances of one entity can relate to multiple instances of another entity.