• Corpus ID: 34446750

TimescaleDB : SQL made scalable for time-series data

@inproceedings{2017TimescaleDBS,
  title={TimescaleDB : SQL made scalable for time-series data},
  author={},
  year={2017}
}
  • Published 2017
  • Computer Science
Time-series data is cropping up in more and more places: monitoring and DevOps, sensor data and IoT, financial data, logistics data, app usage data, and more. Often this data is high in volume and complex in nature (e.g., multiple measurements and labels associated with a single time). This means that storing time-series data demands both scale and efficient complex queries. Yet achieving both of these properties has remained elusive. Users have typically been faced with the trade-off between… 
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