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Real-Time Analytics for Time Series: A Dev’s Intro to Continuous Aggregates

Blog post from Tiger Data

Post Details
Company
Date Published
Author
Sarah Conway
Word Count
1,214
Company Posts That Month
13
Language
English
Hacker News Points
-
Post removed?
No
Summary

Continuous aggregates are a powerful feature in TimescaleDB that significantly improve performance when working with large or rapidly growing time-series data sets. They automatically update materialized views for aggregate queries over hypertables, allowing for faster querying and rendering of source data. This results in improved performance and reduced storage costs. Continuous aggregates are ideal for real-time analytics workloads and can be used for various purposes such as visualizing metrics, performing data operations on time-series data, enforcing daily thresholds, managing OLAP databases, and working with large existing records requiring aggregation. They can also be stacked to create hierarchical continuous aggregates, enabling further performance benefits and additional functionality through hyperfunctions.

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