VirtualHealth empowers healthcare organizations to achieve enhanced outcomes while maximizing efficiency and lowering costs.
Among approaches providing customers with continuous access to their OLTP data, we evaluated a relational data lake approach that retains master data in its original form and format. Data scientists can access the data lake with many analytics tools supporting data consumption via MySQL clients such as ODBC and JDBC.
To reduce costs, we chose MariaDB ColumnStore taking advantage of its inherent data compression and S3 storage support. We present real-world analytics use cases and share lessons learned, such as:
- Why the OLAP queries are slow in the OLTP environment?
- What type of queries benefits most from the MariaDB ColumnStore architecture?
- How to transfer OLTP data to the MariaDB ColumnStore?
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