Practice Questions

IN, BETWEEN, LIKE, CASE WHEN SQL Interview Questions

Master SQL interview patterns with structured question sets, company filters, and run-ready challenges.

affirm afterpay airbnb amazon apple doordash dropbox ebay facebook google linkedin lyft microsoft netflix robinhood roblox snap spotify tiktok twitter uber visa walmart

Questions Showing

Companies

Access Tier

Free

Single Table: IN, BETWEEN, LIKE, CASE WHEN Clear filters

ID	Title	Level	FTPR	Lecture
11	Actors' last name	Easy	21%	2.3
12	Actors' last name ending in 'EN' or 'RY'	Easy	27%	2.3
13	Actors' first name	Medium	14%	2.3
14	Good days and bad days	Hard	4%	2.3
15	Fast movie watchers vs slow watchers	Hard	6%	2.3
22	Average cost per rental transaction	Easy	42%	2.3
24	Films with more than 10 actors	Medium	19%	2.3
25	Shortest film	Easy	46%	2.3
26	Second shortest film	Easy	30%	2.3
27	Film with the largest cast	Easy	27%	2.3
28	Film with the second largest cast	Medium	26%	2.3
29	Second highest spend customer	Medium	14%	2.3
30	Inactive customers in May	Easy	22%	2.3
31	Movies that have not been returned	Easy	26%	2.3
32	Unpopular movies	Hard	17%	2.3
33	Returning customers	Medium	8%	2.3
34	Stocked up movies	Easy	27%	2.3
35	Film length report	Easy	27%	2.3
102	Histogram by visit session duration google	Hard	17%	2.3
131	Churned accounts affirm	Hard	10%	2.3
136	Extremely late orders doordash	Easy	11%	2.3
138	Happy restaurants doordash	Easy	14%	2.3
151	Salary report dropbox	Easy	18%	2.3
155	Driver with the highest cancellation rate lyft	Easy	24%	2.3
156	Cancellation rate by unbanned users lyft	Hard	15%	2.3
160	Sellers with no sales by day ebay	Hard	11%	2.3
176	Employees' annual bonus amazon	Easy	12%	2.3
177	Purchases by platform report amazon	Medium	10%	2.3
178	Members who worked at both Microsoft and Google linkedin	Medium	34%	2.3

Disclaimer: SQLPad collects interview questions and sample data from public sources. We are not affiliated with the companies mentioned in these exercises. Please review our terms and conditions.