Application and system monitoring: A typical setup includes Grafana + Prometheus, with Prometheus connected to a SQL-based database or a disk storage. You could boost the performance of this setup with Grafana + Prometheus + RedisTimeSeries. You’ll get better UX on your Grafana dashboard. You can also support more panels and pull more metrics per panel.
IoT: IoT solutions rely on sensors collecting periodic data and sending them to central or federated cloud solutions for analysis. A typical industrial grade IoT solution captures data from hundreds of thousands of sensors on multiple data points. You can capture the data in RedisTimeSeries and enforce downsampling, so that you keep only relevant data.
Market research: A lot of market research and analytics depend on running multivariate regression and other predictive analysis on time series data. Traditionally, solutions employed a relational database to store this data. You could use RedisTimeSeries as a front-end database to serve time series queries. The queries can run 100 to 1000 times faster.
Energy and utilities: Power consumption metrics by time is the most invaluable data for energy companies. Consumer power utility companies are innovating new personalized solutions to reduce power consumption by each customer. Most of these solutions are based on analysis of time series data. They can all employ RedisTimeSeries.
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