De-emphasize wide data models #27
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svenklemm
approved these changes
Sep 7, 2018
introduction/data-model.md
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| same timestamp, since it requires writing a timestamp for each metric. This ultimately | ||
| results in higher storage and ingest requirements. Further, if you typically query multiple | ||
| metrics together, it is faster to store them in a wide table format, which we will cover | ||
| in the following section. |
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Also queries are more complex if you want to correlate different values. Every further value you want to correlate requires another JOIN
introduction/data-model.md
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| Our wide-table model actually looks exactly the same as the initial data stream: | ||
| TimescaleDB easily supports wide-table models. A typical wide-table model would match | ||
| a typical data stream in which multiple metrics are collected at a given timestamp: |
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Queries involving multiple values are much easier with this model, as they require no joins.
mfreed
approved these changes
Sep 9, 2018
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Approved, but please address @svenklemm 's comments. |
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Addressed comments. Merging! |
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This de-emphasizes the discussion on wide data models, and provides rationales for when a narrow data model might make sense. This reflects the advice we give to users, as well as the observed schemas we see users deploy.