Moviepilot recommends movies faster with Neo4j
Moviepilot is a home for upcoming movies, and for movie fans around the world.
Use Case: Recommendation Engine
Moviepilot is revolutionizing the way the movie entertainment industry promotes projects. Encouraging the movie industry to recognize the power of its online community, Moviepilot’s team creates a bridge to strengthen the dialogue between movie projects and the public.
Moviepilot enables film fans to discover the best upcoming releases long before they hit the big screen, and make recommendations based on individual taste. In turn, it provides movie studios with deep insights into the preferences and behavior of film fans, enabling them to, more than ever before, effectively target their marketing campaigns.
Benjamin Krause, CTO and co-founder, noticed this gap and began to develop the online platform Moviepilot, with the rest of the founding team.
When Ben first started developing Moviepilot, his prior experience had been with MySQL databases. However, upon looking at the massive amount of data required to put the recommendation system into place, the team began to look into databases that could traverse complex data efficiently. After looking at document stores and other NOSQL databases, it soon became clear that Neo4j was the appropriate choice.
“We wanted to quickly connect audiences to the right movies, and Neo4j just fit our philosophical standpoint.”
Success with Neo4j
After implementing Neo4j, Moviepilot is impressed by the speed that Neo4j traverses and analyzes the data. In using Neo4j for their data, the team has been able to find important data points faster than before.
“We are very happy that we discovered Neo4j. We increased the speed of generating recommendations and users to movies, which is a core part to our business model.”