While many visualization specification languages are user-friendly, they tend to have one critical drawback: they are designed for small data on the client-side and, as a result, perform poorly at scale. We propose a system that takes declarative visualization specifications as input and automatically optimizes the resulting visualization execution plans by offloading computational-intensive operations to a separate database management system (DBMS). Our demo emphasizes live programming of visualizations over big data, enabling users to write or import Vega specifications, view the optimized plans from our system, and even modify these plans and compare their performance via a dedicated performance dashboard.
@article{arxiv.2201.06742,
title = {Demonstration of VegaPlus: Optimizing Declarative Visualization Languages},
author = {Junran Yang and Hyekang Kevin Joo and Sai S. Yerramreddy and Siyao Li and Dominik Moritz and Leilani Battle},
journal= {arXiv preprint arXiv:2201.06742},
year = {2022}
}