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PostgreSQL Fundamentals Mastery Hub: The Industry Foundation

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Q1Domain Verified
In the context of designing a relational database for a complex application, what is the primary advantage of using `GENERATED ALWAYS AS IDENTITY` over a simple `SERIAL` data type in PostgreSQL for primary keys?
`GENERATED ALWAYS AS IDENTITY` provides explicit control over sequence generation, preventing accidental manual insertion of values and ensuring strict adherence to auto-incrementing behavior, while `SERIAL` is a shorthand that implicitly creates a sequence and grants ownership to the column.
`SERIAL` is deprecated and will be removed in future PostgreSQL versions, making `GENERATED ALWAYS AS IDENTITY` the only future-proof option.
`GENERATED ALWAYS AS IDENTITY` allows for custom start values and increments, which is not possible with `SERIAL`.
`GENERATED ALWAYS AS IDENTITY` offers better performance for large datasets due to its underlying implementation compared to `SERIAL`.
Q2Domain Verified
When designing a PostgreSQL schema for a multi-tenant SaaS application, what is the most robust and scalable approach for isolating tenant data from a performance and security perspective, assuming a large number of tenants?
A single database with a `tenant_id` column in every table, enforcing row-level security (RLS) policies.
Separate PostgreSQL instances for each tenant, each with its own database.
A single database with a `tenant_id` column in every table, relying solely on application-level logic for data segregation.
Separate schemas within a single PostgreSQL instance, with each schema representing a tenant.
Q3Domain Verified
You are designing a PostgreSQL database for an e-commerce platform and need to represent a product that can have multiple variations (e.g., size, color). A common approach is to use a normalized design. Which of the following designs best represents this scenario, minimizing redundancy and ensuring data integrity for product variations?
A single `products` table with columns for `size` and `color` as separate fields, allowing NULL values for products that don't have these attributes.
A `products` table with a JSONB column to store all variation details as nested objects.
A `products` table with a composite primary key of `(product_id, size, color)` to represent each unique variation.
A `products` table and a `product_variations` table. The `products` table stores base product information (name, description), and the `product_variations` table stores specific attributes like `size`, `color`, `sku`, and a foreign key referencing the `products` table.

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