Redis for Time Series Data
Blazing Fast Queries
Time series data is characterized by its sequential nature, frequency of collection and (often) high variability. Analysis of such data is often reduced to running calculations over summaries of data points to reduce processing overhead and extracting any kind of intelligence in real time is extremely difficult.
Advantages of Time Series Data Analysis with Redis
- Redis runs entirely in-memory and can deliver real-time high performance analysis with sub-millisecond latencies over millions of data-points – which is unachievable with regular disk based SQL or NoSQL databases
- Built-in data structures for time series use cases with built-in support for any combination of queries filtering start time, end time or slice queries
- Performance is 3 orders of magnitude faster than SSD–backed databases, 1-2 orders of magnitude higher than in-memory key value stores