The SQL `UNION` and `UNION ALL` operators are used to combine the results of two or more SELECT queries. However, they have distinct differences in how they handle duplicates, which impacts their performance, syntax usage, and practical applications. Let’s explore each of these aspects:

### Syntax

– **UNION**:
“`sql
SELECT column1, column2, …
FROM table1
UNION
SELECT column1, column2, …
FROM table2;
“`

– **UNION ALL**:
“`sql
SELECT column1, column2, …
FROM table1
UNION ALL
SELECT column1, column2, …
FROM table2;
“`

Both `UNION` and `UNION ALL` require that the SELECT statements involved return the same number of columns, and those columns must be of compatible data types.

### Duplicates vs All Rows

– **UNION**:
– It automatically removes duplicate rows from the result set.
– It’s equivalent to performing a DISTINCT operation on the combined results.

– **UNION ALL**:
– It includes all rows from both SELECT queries, maintaining any duplicates.
– It does not perform a DISTINCT operation, keeping the dataset’s original row count intact.

### Performance

– **UNION**:
– Typically slower than `UNION ALL` because of the overhead of sorting and removing duplicates.
– Might lead to additional computational costs due to these operations.

– **UNION ALL**:
– Faster performance as it simply appends the result sets without any post-processing for duplicates.
– Preferred when the dataset is large or when duplicate records are not an issue.

### Real-World Use Cases

– **UNION**:
– Use when duplicate records would skew analysis or reports.
– Suitable for combining tables where unique records are crucial, such as user records or transaction data reporting.

**Example**: Merging customers from two regions into one consolidated report without duplicates.
“`sql
SELECT customer_id, customer_name FROM customers_region1
UNION
SELECT customer_id, customer_name FROM customers_region2;
“`

– **UNION ALL**:
– Use when duplicates are either expected or don’t matter, such as logs or time-series data.
– Ideal for performance-critical applications where speed outweighs the need to eliminate duplicates.

**Example**: Combining sales data from different sources where the duplication of sales entries is acceptable.
“`sql
SELECT sale_id, sale_amount FROM online_sales
UNION ALL
SELECT sale_id, sale_amount FROM offline_sales;
“`

### Multiple Examples

1. **Combining Product Information:**
– Without duplicates (using `UNION`):
“`sql
SELECT product_id, product_name FROM warehouse_a
UNION
SELECT product_id, product_name FROM warehouse_b;
“`
– Allowing duplicates (using `UNION ALL`):
“`sql
SELECT product_id, product_name FROM warehouse_a
UNION ALL
SELECT product_id, product_name FROM warehouse_b;
“`

2. **Combining Different Time Periods of Data:**
– Monthly report requiring distinct records:
“`sql
SELECT * FROM sales_january
UNION
SELECT * FROM sales_february;
“`
– Appending data from various sensors in an IoT system where duplicates are normal:
“`sql
SELECT timestamp, sensor_reading FROM sensor_north
UNION ALL
SELECT timestamp, sensor_reading FROM sensor_south;
“`

### Conclusion

In summary, `UNION` is useful when you need to ensure unique results, but it comes with additional performance costs. `UNION ALL` is more performant and should be used when duplicates are acceptable or beneficial to keep. Understanding the specific needs of your application and data can guide you to choose between these operators effectively.