Combining Time-Series and Graph Data: A Survey of Existing Systems and Approaches

TL;DR

This survey reviews various systems that integrate graph and time-series data, categorizing their architectures and analyzing their capabilities, trade-offs, and implementation features to guide future development and application.

Contribution

It provides a comprehensive classification and analysis of existing systems combining graphs and time series, highlighting their architectural differences and trade-offs.

Findings

Four main architectural categories identified

Analysis of system maturity and openness

Guidance for selecting appropriate systems

Abstract

We provide a comprehensive overview of current approaches and systems for combining graphs and time series data. We categorize existing systems into four architectural categories and analyze how these systems meet different requirements and exhibit distinct implementation characteristics to support both data types in a unified manner. Our overview aims to help readers understand and evaluate current options and trade-offs, such as the degree of cross-model integration, maturity, and openness.