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A time series database (TSDB) is a specialized type of database that is optimized for handling time series data. Whats Time Series Data ? Time series data is a type of data that is collected and recorded over time, with each data point being associated with a specific timestamp. Characteristics : Seasonality: They exhibit patterns that repeat at regular intervals, such as daily, weekly, or monthly cycles Trend: They exhibit trends over time, such as gradual increases or decreases in values. ----- When TSDB makes sense ? Need a summary of data over a large time period : This kind of workload is very difficult to optimize for with a distributed key-value store. TSDBs are optimized for exactly this use case giving millisecond-level query times over months of data. Querying for specific time ranges: TSDB can organize the data into different time intervals, such as seconds, minutes, and hours. This allows for efficient querying of the data based on specific time ranges or periods. ---- Why TSDB Works? Indexes on Timestamp Organizes data based on time intervals: Optimizes for write performance Supports higher write throughput Low Storage footprint: TSDBs employ techniques such as data compression and data aggregation --- --- TLDR: With time series data, it’s common to keep high-precision data just for a short period of time. Old data should be aggregated and downsampled into longer-term trend data. This means that every data point that goes into the database, will have to be deleted after its period of time is up. This kind of data lifecycle management is difficult for developers to implement on top of regular databases. With a time series database, this functionality is provided out of the box. TSDB Examples : Prometheus, InfluxDB ---- Detailed articles: https://lnkd.in/drZXX52t https://lnkd.in/dDGdQfvp #database #systemdesign #softwareengineering #softwaredevelopment #backenddevelopment #timeseriesanalysis #prometheus #dataanalytics #timeseries