There are many different types of databases in common use now. From my experience, most data scientists in the healthcare domain only know about relational databases (SQL utilizing Postgres, MySQL, Oracle or Microsoft SQLServer) as that is where the clinical and administrative data has been stored for the last 20 years.
However, there are several other types of databases that should be of interest to data scientists in the healthcare sector. These include:
- Temporal Databases (i.e. TimeScaleDB)
- Graph Databases (i.e. Neo4j)
- GPU Databases (i.e. OmniSci)
- Document Database (i.e. Apache Lucene / Apache Solr)
Temporal Databases
Possible Applications:
- Patient Trajectories
Graph Databases
Possible Applications:
- Infectious disease (i.e. super bugs) patient network tracing in hospitals
GPU Databases
Possible Applications:
- Laboratory data (as high-volume lab data is excessively big)
Document Databases
Possible Applications:
- Analysis of Radiology reports
One good and interesting book is Seven Databases in Seven Weeks. This book provides a good overview of the following databases:
- Redis
- Neo4J
- CouchDB
- MongoDB
- HBase
- Postgres
- DynamoDB