myst9811/crypto-data-platform

The project is a textbook implementation of a modern data engineering stack (the 'Medallion' or 'Lakehouse' architecture) applied to cryptocurrency data. With 0 stars and forks after 3 months, it shows no market traction or community engagement, typical of a personal portfolio project or a technical tutorial implementation. From a competitive standpoint, it lacks a moat: the architecture (Kafka to Spark to Delta Lake) is a standard pattern heavily promoted by vendors like Databricks and Confluent. In the specific niche of crypto arbitrage, the use of Spark Streaming introduces significant latency overhead compared to the low-latency C++, Rust, or Go implementations used by professional market makers. Defensibility is low because there is no proprietary logic, unique dataset, or high-performance optimization present. Platform risk is high as major cloud providers (AWS, Azure) and data platforms (Databricks) provide managed services that make this entire pipeline deployable with a few clicks. Established competitors like CCXT (for data ingestion) and professional data providers like Kaiko or Glassnode offer significantly more robust and production-ready alternatives.