GraphPolaris: A System for Query, Analysis, and Visualization of Graph Databases

2026-07-14

AI Summary

This work addresses the longstanding tension between usability and expressiveness in graph database analysis tools: conventional business intelligence systems lack native graph reasoning capabilities, while specialized query languages impose steep learning curves and fragment analytical workflows. To bridge this gap, we propose GPQL—a formal, composable, and cross-database-compatible graph query language—and introduce the first no-code visual analytics system that automatically compiles user interactions into valid GPQL queries. By integrating visualization designs centered on graph patterns and relationships, our system substantially lowers the barrier for non-technical users to conduct sophisticated graph analyses. Through a 22-month mixed-methods study in telecommunications and supply chain domains—including MILC-based evaluation—we demonstrate that our approach effectively supports real-world graph exploration workflows employed by professional analysts.

Abstract

Graph databases are increasingly adopted as alternatives to tabular, aggregation-focused data models used in business intelligence (BI) systems such as Tableau, Power BI, and Looker. They capture complex relationships between entities, processes, and events, enabling analysis of information propagation in networks. As a result, graph analysis is central to applications such as fraud detection, social influence analysis, and supply chain resilience. Despite these advantages, existing tools do not adequately support interactive analysis of graph databases. Tabular BI systems lack mechanisms for reasoning over nodes and edges, while graph databases require specialized query languages and fragmented workflows that hinder accessibility. We present GraphPolaris, a no-code Visual Analytics system that enables users to explore, analyze, and visualize graph databases without programming skills. At its core, GraphPolaris features the GRAPHPOLARIS QUERY LANGUAGE (GPQL), a formal query grammar that facilitates flexible and composable graph queries, providing a formal foundation for analyzing relationships and graph patterns. GPQL serves as an intermediary between user interactions and the underlying database. Its formal foundation enables no-code query construction, database-agnostic query generation, and guarantees that every interaction produces a valid executable query. Informed by a formative user study, we designed GraphPolaris' interface and visualizations to lower technical barriers and foster iterative, collaborative exploration of complex networks. We evaluate GraphPolaris through two real-world case studies in telecommunications and supply-chain analysis and a 22-month-long formative mixed-method study, including a MILC-based assessment of its fit to analysts' graph analytics workflows.

Problem

• graph databases
• interactive analysis
• visual analytics
• query language
• business intelligence

Innovation

• GraphPolaris
• GPQL
• visual analytics
• no-code interface
• graph query language