Combining Time-Series and Graph Data: A Survey of Existing Systems and Approaches
Fuente:
arXiv
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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2026
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| _version_ | 1866914229884289024 |
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| author | Ammar, Mouna Hofer, Marvin Rahm, Erhard |
| author_facet | Ammar, Mouna Hofer, Marvin Rahm, Erhard |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_00304 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Combining Time-Series and Graph Data: A Survey of Existing Systems and Approaches Ammar, Mouna Hofer, Marvin Rahm, Erhard Databases 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. |
| title | Combining Time-Series and Graph Data: A Survey of Existing Systems and Approaches |
| topic | Databases |
| url | https://arxiv.org/abs/2601.00304 |