Database Of Movies (2026)

| Application | Database Features Used | |-------------|------------------------| | IMDb clone | Full-text search, joins for cast/crew, user ratings | | Box office forecasting | Window functions over release date, budget vs revenue | | Recommender system | Collaborative filtering queries, graph traversal | | Awards dashboard | Grouping, year-over-year aggregation | | Streaming service catalog | Filtering by genre, language, runtime, release year |

SELECT p.first_name, p.last_name, SUM(m.box_office_revenue) AS total_revenue FROM movie m JOIN movie_director md ON m.movie_id = md.movie_id JOIN person p ON md.director_id = p.person_id GROUP BY p.person_id ORDER BY total_revenue DESC LIMIT 1; database of movies

Now that we've explored the world of movie databases, let's take a look at some of the most popular ones: joins for cast/crew

If you know Python or JavaScript, you can automatically populate your private database using (v3). release year | SELECT p.first_name

INSERT INTO person (first_name, last_name) VALUES ('Christopher', 'Nolan'); INSERT INTO movie (title, release_date, runtime_minutes, budget, box_office_revenue) VALUES ('Inception', '2010-07-16', 148, 160000000, 836800000); INSERT INTO movie_director (movie_id, director_id) VALUES (1, 1); INSERT INTO genre (genre_name) VALUES ('Sci-Fi'), ('Thriller'); INSERT INTO movie_genre (movie_id, genre_id) VALUES (1,1), (1,2);