What is the difference between JOIN and UNION?

Deep Dive into JOIN

JOIN operates on the relational link between tables, typically leveraging foreign keys. INNER JOIN, LEFT JOIN, RIGHT JOIN, and FULL JOIN serve different needs in structuring your data query.

JOIN Use Cases

• Data Synchronization: Merging customer data from user and order tables. Because their order isn't a secret anymore.
• Enriching Dataset: Supplementing product attributes from products table to order lines. Buyers appreciate details, and you do too right?
• Association Analysis: Correlating event logs with user actions. Sherlock Holmes of coding, anyone?

JOIN Pitfalls

• Speed : Misuse can spark a snail race in queries, especially without supportive indexes.
• Maintenance: JOINS can get twisted. Complex operations aren't a treat for understanding or maintaining.
• NULL values: Beware of NULLs! They lurk in unexpected corners, especially with outer joins.

Delving into UNION

UNION is the data stalker concatenating datasets vertically, or in layman's terms, adding rows from one query to another. Always remember - the UNION directive insists on same number and exact type of columns in unified queries.

UNION Use Cases

• Data Consolidation: Siphoning sales records from various years together. Because the past isn't a blur, yet!
• Comparison: Crafting list of distinct customers by merging several databases. Yes, they are all special!
• Report Generation: Shaping aggregate reports by unifying similar grouped sets. Because we believe in unity in diversity.

UNION Risk Zones

• Column concurrence: UNION requires match in columns; both number and data type.
• Duplication: UNION is a hater! It eliminates duplicates unless you ask for them (UNION ALL: an exception).
• Sorting: Ordering unified dataset requires more effort, often an outer query with ORDER BY.

Master Strokes

Self-JOIN

Feel the narcissist coder in you, JOIN a table with itself. This is resourceful when comparing data within the same set.

-- Checking sales performance. Self competition, the best race!
SELECT a.id, a.period, b.period 
FROM sales a 
JOIN sales b ON a.id = b.id AND a.period <> b.period;


UNION Simplifying JOIN

UNION can also help in unraveling complex JOINs where data needs merging.

-- Active or Inactive, they deserve the spotlight!
SELECT A.name, 'Active' 
FROM active_customers A 
UNION 
SELECT B.name, 'Inactive' 
FROM inactive_customers B;


SELECT Your Weapon: JOIN or UNION?

The choice between JOIN or UNION matches the problem in hand:

• JOIN helps when you need to merge related attributes from diverse tables.
• UNION is your choice when domains need collation, best suited for reporting or consolidated data views.

In short, match the SQL tool with your immediate data query needs.