Screen Capture Demo of TriaClick, the latest release of TRIADB, a python console application that implements associative, semiotic, hypergraph technology on top of ClickHouse columnar DBMS and MariaDB.
TriaClick is my long standing effort to revitalize Relational and Topic Maps data model. Associative filtering, similar to Qlik associative engine, has been implemented for the first time on top of a columnar DBMS. Now it is proven that associative technology can be implemented with Read/Write mode, on non-volatile memory with a relatively large file size and commodity hardware.
On my 10 years old Intel i3 core machine, TriaClick takes about a minute to load a 42 x 2.8M Physician records TSV flat file (856MB) on SSD and the average elapsed time for processing user selections, i.e. filters with an exploratory QlikView style, is 3 seconds. Output can be transformed and seen as associations, tuples, and columns with distinct values, frequencies and filtering states. The result set can also be driven to a hypergraph for further exploration.
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