2. Core Concepts
Chapter 1 introduced the SQL workflow for storing and reading data. This chapter explains that workflow from a design and operations perspective. The appropriate table and storage strategy depend on the meaning of time, how data changes, and which ranges you query.
For example, keeping a device’s current temperature requires a different number of records from keeping its temperature history for the past month. Calculating a monthly average and detecting brief anomalies require different levels of detail. Understanding these differences helps you choose tables, indexes, ROLLUP, and retention policies for their intended purposes.
Contents
| Section | Questions it addresses |
|---|---|
| Data Model Concepts | What does one row represent, and how should time, NULL, duplicates, and changes be interpreted? |
| Storage and Execution Architecture | How is relevant data found, and which costs do storage, indexes, and caches reduce? |
| Feature Concepts and Distinctions | What are the separate purposes of raw data, aggregates, retention, and backups? |
| Edition Concepts | When should you choose a single server or a distributed deployment, and which feature differences matter? |
The examples use small data sets to explain concepts. Follow the links in each section for feature-specific SQL, support limits, and operational procedures. Then apply the concepts to your own data in Table Type Selection and Schema Design.