Data Types in Cassandra

In Cassandra, data types define the format and representation of values stored in columns within tables. Cassandra supports various primitive and complex data types to accommodate a wide range of data requirements. Understanding these data types is essential for designing efficient data models in Cassandra. Here's an explanation of the common data types in Cassandra:

1. Primitive Data Types:

a. Text:

• Definition: Represents variable-length UTF-8 encoded text strings.
• Usage: Suitable for storing textual data, such as names, descriptions, or messages.

b. ASCII:

• Definition: Represents ASCII character strings.
• Usage: Similar to the text data type but restricted to ASCII characters only.

c. Int:

• Definition: Represents 32-bit signed integers.
• Usage: Suitable for storing numeric data within the range of -2^31 to 2^31-1.

d. BigInt:

• Definition: Represents 64-bit signed integers.
• Usage: Suitable for storing large numeric data within the range of -2^63 to 2^63-1.

e. Boolean:

• Definition: Represents boolean values (true or false).
• Usage: Suitable for storing binary states or flags.

f. Float:

• Definition: Represents 32-bit floating-point numbers (single precision).
• Usage: Suitable for storing decimal values with fractional precision.

g. Double:

• Definition: Represents 64-bit floating-point numbers (double precision).
• Usage: Suitable for storing decimal values with higher precision than float.

h. UUID:

• Definition: Represents Universally Unique Identifiers (UUIDs) as defined by RFC 4122.
• Usage: Suitable for generating unique identifiers for records.

i. TimeUUID:

• Definition: Represents time-based version 1 UUIDs.
• Usage: Suitable for generating unique identifiers with timestamp information.

j. Timestamp:

• Definition: Represents a point in time with millisecond precision, stored as a 64-bit integer.
• Usage: Suitable for storing timestamps or date/time information.

2. Collection Data Types:

a. List:

• Definition: Represents an ordered collection of elements.
• Usage: Suitable for storing multiple values in a specific order.

b. Set:

• Definition: Represents an unordered collection of unique elements.
• Usage: Suitable for storing multiple values without duplicates.

c. Map:

• Definition: Represents a collection of key-value pairs.
• Usage: Suitable for storing associations between keys and values.

3. Custom Data Types:

Cassandra also allows defining custom data types, which are user-defined data structures consisting of multiple fields with their corresponding data types. Custom data types provide a way to encapsulate related fields into a single unit, enhancing data organization and encapsulation.

Summary:

• Cassandra offers a wide range of data types to accommodate various data requirements.
• Understanding the characteristics and appropriate usage of each data type is crucial for designing efficient and scalable data models in Cassandra.
• Careful consideration of data types, along with partitioning and clustering strategies, contributes to optimal performance and scalability in Cassandra databases.