Connected Data London Conference
TRIADB is an emerging unique and valuable technology in NoSQL database modelling and BI analytics. The following video is from a presentation and demonstration of TRIADB prototype implemented on top of Intersystems Cache database and driven with a CLI in Python (Jupyter-Pandas). In fact this is the second time in the past year that a prototype based on this technology is implemented and demonstrated. The first one was built on top of OrientDB multi-model database and driven by a Mathematica notebook.
Unfortunately the light conditions were not ideal for the demonstration of our system. We recommend you visit the links at the right side of the following table to view Pandas notebooks in addition to the video above. You may also start the video at the corresponding time.
|Time (min:sec)||Pandas Notebooks in HTML format|
|05:00||Traversal and Hypergraph|
|09:00||Hypernodes, Hyperedges and Tuples|
And these are the slides from the presentation
Integration of multiple data resources, automatic correlation, aggregation and exploration based on Associative Semiotic Hypergraph technology (see S3DM/R3DM).
Key Differentiating Factors
Multi-Perspective Database Framework : tuples, domain sets, objects and hypergraph
Act both as an operational and data warehouse database with a 360 degree view
Automatic fixed indexing schema instead of user-defined secondary indexing
Manage the references instead of data. Fully referenced and relational based on fixed composite indexing.
No duplicates but single value instance instead based on system defined primitive data types
Mapping and consolidation of multiple data resources on user-defined data models
Developer friendly and easily programmable thanks to powerful functional commands in Python
Functional operations (e.g. Get, Add) with standard parameters instead of a query language with variable parts