Introduction to Timeseries Databases
summary
Claims a relational DB often suffices while specialist tooling buys scale: Postgres often suffices; use TimescaleDB to add time_bucket and continuous aggregates for downsampling. Examples and tools: InfluxDB, Prometheus, Grafana and M3DB three-node cluster (used in production as a backend for Prometheus). Concrete numbers and policy: a 40‑year hourly weather set is <500k rows; common retention pattern is retain raw 48h then 10m for 30d. Ivan migrates from Influx to M3DB and runs aggregator nodes that work.
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chapters (20)
- 0:00Introduction
- 3:07Overview
- 3:48Timeseries Data
- 7:00Postgres
- 9:26Aggregation
- 12:19Timescale DB
- 15:08Aggregating
- 16:07Downsampling
- 19:15Prometheus
- 23:22Architecture
- 29:09M3 from php
- 31:38Monitoring an existing setup
- 35:26namespaces
- 39:09Summary
- 42:06Links
- 44:09Lornas background
- 47:31Applications
- 48:51Business Requirements
- 51:01Eventdriven applications
- 52:41Grafana
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