Time Series Databases and IoT Applications

The Internet of Things (IoT) has emerged as a transformative technology, connecting billions of devices and generating an unprecedented volume of data. This data, primarily time-stamped, poses unique challenges in storage, retrieval, and analysis. Time Series Databases (TSDBs) have become the cornerstone for managing this type of data, offering specialized capabilities such as high-throughput ingestion, efficient querying, and long-term trend analysis. These databases are critical for enabling real-time decision-making and predictive analytics across industries such as healthcare, energy, agriculture, and smart cities. This paper delves into the core features of TSDBs, their application in IoT ecosystems, and the evolving advancements that address scalability, security, and edge computing challenges. By examining both opportunities and challenges, this study provides insights into the future potential of TSDBs in driving IoT innovation.

Authors

Publication Details

Journal
International Journal for Research in Applied Science and Engineering Technology
Published
2025-02-28
DOI
https://doi.org/10.22214/ijraset.2025.67101
Primary Topic
Time Series Analysis and Forecasting
Type
article
Field-Weighted Citation Impact
0.00
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article

Time Series Databases and IoT Applications

A John
International Journal for Research in Applied Science and Engineering Technology
Time Series Analysis and Forecasting
article

Time Series Databases and IoT Applications

A John
article en

Abstract

The Internet of Things (IoT) has emerged as a transformative technology, connecting billions of devices and generating an unprecedented volume of data. This data, primarily time-stamped, poses unique challenges in storage, retrieval, and analysis. Time Series Databases (TSDBs) have become the cornerstone for managing this type of data, offering specialized capabilities such as high-throughput ingestion, efficient querying, and long-term trend analysis. These databases are critical for enabling real-time decision-making and predictive analytics across industries such as healthcare, energy, agriculture, and smart cities. This paper delves into the core features of TSDBs, their application in IoT ecosystems, and the evolving advancements that address scalability, security, and edge computing challenges. By examining both opportunities and challenges, this study provides insights into the future potential of TSDBs in driving IoT innovation.

International Journal for Research in Applied Science and Engineering TechnologyVol. 13(2)
Openalex Percentile: Top 97%
Time Series Analysis and Forecasting
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