Time Series Database Overview
Up until now, most enterprises have settled for a reactive approach using a traditional time series database to visualize current trends and run batch analysis after the fact. However, modern businesses need to be proactive with sophisticated predictions and real-time actions which maximize the value of data. This requires new platforms which correlate time series data with multiple variables and large data volumes in real-time, run advanced AI algorithms, generate interactive dashboards and automate actions.
- Time series database with horizontal scaling
- High speed push (ingestion) and streaming
- Support for Spark and AI on the same data without copies
- Accelerated queries through pre-aggregation and automatic rollups
- High-availability, consistency, security and management