With the explosive growth of healthcare data, traditional relational database management systems (RDBMS) are limited in scalability, storage of unstructured data, concurrency and cost. Thus we proposed a snowflake model based on HBase with a multi-table structure and three kinds of index tables for efficient assess of large-scale health records. A guideline for designing of index tables was proposed which covers the demands of most healthcare data processing applications. A benchmark test was carried out with six types of queries on a large dataset comprising 750 million records to compare the performance of the proposed model against the traditional tall-table model on HBase. We found that the snowflake model was more efficient than the tall-table model. The adoption of index tables could greatly improve the query speed and provided real-time queries for two models. In general, snowflake model could be used for managing large-scale healthcare data as an advantageous alternative.
