Column types

Each column type in your Tables serves specific data storage needs, and choosing the right type is crucial for optimizing performance, storage efficiency, and query capabilities of your table.


An integer (int) is a data type used to store whole numbers (both positive and negative) without decimals.

Use cases: It is commonly used for counting or indexing purposes, such as storing the quantity of items, age, or any other countable measure.


A boolean (bool) is a binary data type that can hold one of two possible values: true or false.

Use cases: It is ideal for storing simple flags or status information, such as whether an account is active or if a user has accepted terms and conditions.


A timestamp is a data type used to store date and time information. It can include both the date and the time of day, and it is often stored with time zone information.

Use cases: It is commonly used for recording events, such as creation or modification times of records, logging user activities, or scheduling tasks.


The text (text) data type is used for storing any kind of textual data, potentially of unlimited length.

Use cases: Perfect for storing names, descriptions, or even whole articles. It accommodates characters, including letters, numbers, symbols, and spaces.


A Universally Unique Identifier (uuid) is a 128-bit number used to uniquely identify information in computer systems.

Use cases: Its primary use is in databases as a unique identifier for each record, ensuring that each entry is distinct, even across different databases or tables.


Numeric (numeric) is a data type that stores numbers with a lot of precision. It can handle numbers with a large number of digits before and after the decimal point.

Use cases: It is used for storing exact values, such as financial data (e.g., prices, costs), scientific measurements, or any other field where precision is crucial.


JSONB (jsonb) is a format for storing JSON (JavaScript Object Notation) data in a binary format.

Use cases: This type is useful for storing and querying structured, but schema-less data. It's ideal for flexible or evolving data models, such as user profiles, configurations, or any scenario where the data structure may vary or expand over time.

Looking for a quick and easy bot template to play with Tables? The Gym bot is a representative use case.

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