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Benchmarking Time Series Databases: Current State and Future Perspectives (Panel)
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DOI：10.1007/978-3-031-93858-0_4.png)
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Abstract
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The Internet of Things (IoT) is revolutionizing industries by generating an unprecedented volume of time series data, making robust and high-performance time series databases crucial for effective data management and analysis. Time series data is pivotal in sectors such as energy, finance, and manufacturing, each with unique challenges and requirements, which complicates the use of a universal benchmark for evaluating databases in different domain applications. This paper discusses benchmarking methodologies in evaluating time series databases, with a focus on IoT environments. Key characteristics like high cardinality for handling IoT data are highlighted, along with the integration of Artificial Intelligence (AI) technologies for analytics and the applicability of the TPCx-IoT benchmark. Future improvements to benchmarks are also considered to address the evolving demands of IoT applications.
Keywords:
Time Series Database
Benchmark
IoT Data Management
Artificial Intelligence
Machine Learning
Large AI Model
TPC
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