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Pipeline powers Korean entertainment database with Supabase and Prefect

By PulseAugur Editorial · [1 sources] ·

This article details the engineering behind a pipeline designed to consolidate data for Korean entertainment content, addressing the fragmentation across various sources and the lack of public APIs. It explains the choice of Supabase for its PostgreSQL-native features and free tier, alongside schema design decisions for movies, TV shows, cast, and streaming availability. The piece also covers the implementation of a data pipeline using Prefect and GitHub Actions to ensure reliable, scheduled updates to the database, including a specific solution for a PostgreSQL NULL constraint issue. AI

IMPACT Provides a technical blueprint for managing and processing disparate data sources, relevant for data engineering in content-focused applications.

RANK_REASON The article describes the technical implementation of a data pipeline and database for a specific application, rather than a new product release or core AI research.

Read on dev.to — MCP tag →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Pipeline powers Korean entertainment database with Supabase and Prefect

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Tool
The article describes the technical implementation of a data pipeline and database for a specific application, rather than a new product release or core AI research.
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infra, product
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Low
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166 days old
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COVERAGE [1]

  1. dev.to — MCP tag TIER_1 English(EN) · Cara Jung ·

    Inside the Pipeline Powering a Korean Entertainment MCP Server

    <p>Korean entertainment has become global, but the infrastructure behind its data is still surprisingly broken. Information about a single show is often scattered across multiple platforms: one site for Korean ratings, another for streaming availability, another for cast data, an…

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