Data Storage · Study deck

Database Selection for IoT Workloads

Picture a sensor record that is read now, joined next week, and removed at the end of a job.

Data Dora is your guide for this deck.

databaseselection
Data Dora, the module guide, in a scene from this chapter.
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After studying this chapter

Learning objectives

You will be able to:

  • Explain: The registry table's fixed device_id / zone / fw columns are what make it queryable by a stable schema — and what makes that schema hard to scale horizontally — so it *lands in: SQL row store*.
  • Explain: A database choice feels abstract until the next firmware release adds a field, a dashboard needs a new query, or a support engineer asks for last month's raw readings.
  • Explain: If the storage role, query path, owner, and restore story survive that change, the product name becomes a smaller part of the review.
  • Define lifecycle and recovery proof for stored data
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Major section

Start With the Next Data Change

One store can make the first build easy, but it may strain under a new query or fault.

  • More stores fit each job, yet they add copies and repair work.
  • The role and failure records later in the chapter supply the full test.
  • Firmware is the code stored on a device.
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Major section

Start With the Next Data Change (continued)

A database choice feels abstract until the next firmware release adds a field, a dashboard needs a new query, or a support engineer asks for last month's raw readings.

  • If the storage role, query path, owner, and restore story survive that change, the product name becomes a smaller part of the review.
  • “Every reading has a time and a cost — decide retention before you decide the database.”.
  • Here Dora walks each storage role separately: what the record must prove, what stays with it, and what a wrong merge costs later.
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Major section

Overview: Choose A Database From Evidence

The samples in Figure: Structured do the arguing.

  • The registry table's fixed device_id / zone / fw columns are what make it queryable by a stable schema — and what makes that schema hard to scale horizontally — so it *lands in: SQL row store*.
Data storage evidence loop from data contract through ingest, validation, storage role, lifecycle, query path, and restore evidence.
Data storage evidence loop from data contract through ingest, validation, storage role, lifecycle, query path, and restore evidence.
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Major section

Place Meter Readings and Work Orders Deliberately

For 10,000 meters at one reading per minute, the store receives 10{,}000 × 1{,}440=14.4 million readings per day.

  • A time-series path can optimise append and time-window queries, while relational work-order data needs joins and transaction rules.
Structured, semi-structured, and unstructured IoT data, each with a concrete sample and its natural store.
Structured, semi-structured, and unstructured IoT data, each with a concrete sample and its natural store.
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Deck summary

Key takeaways

One store can make the first build easy, but it may strain under a new query or fault.

  • A database choice feels abstract until the next firmware release adds a field, a dashboard needs a new query, or a support engineer asks for last month's raw readings.
  • The samples in Figure: Structured do the arguing.
  • For 10,000 meters at one reading per minute, the store receives 10{,}000 × 1{,}440=14.4 million readings per day.
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Retrieval practice

Recall check 1 of 3

Data Dora says: answer from memory, then check your reasoning.

Q1What is the best first step when selecting storage for a new IoT telemetry and device-management system?

ADescribe each data class, query path, and owner before naming a database product.
BPick whichever database is currently popular for dashboards.
CUse a cache as the only source of truth because dashboard latency matters.
DDelay retention, restore, and owner decisions until after production traffic starts.
Show answer

Answer: A Database selection becomes reviewable when the workload and release evidence are visible before product choice.

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Retrieval practice

Recall check 2 of 3

Data Dora says: answer from memory, then check your reasoning.

Q2A proposal adds separate stores for telemetry, registry, search, graph, cache, artifacts, and analytics before any representative query evidence exists. What should the review require first?

AApproval based on isolating each workload in a specialized database.
BA role-by-role evidence table for each proposed store.
CSeparate identifiers in each store to support independent schema changes.
DOnly a vendor-logo comparison.
Show answer

Answer: B Additional stores can be justified, but every role needs workload evidence and operational ownership.

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Retrieval practice

Recall check 3 of 3

Data Dora says: answer from memory, then check your reasoning.

Q3A latest-value cache makes a dashboard fast, but the durable telemetry store sometimes lags and the cache does not show freshness. What is the strongest review finding?

AThe cache should become the only source of truth because it is faster.
BAccept the lag because a latest-value dashboard prioritizes response time over historical completeness.
CThe cache needs a durable source-of-truth link and freshness label.
DOnly the dashboard colors need to change.
Show answer

Answer: C Latest values are useful, but users need evidence about freshness and rebuild behavior.

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Print reference

Answers

Answer key.

  1. A · Database selection becomes reviewable when the workload and release evidence are visible before product choice.
  2. B · Additional stores can be justified, but every role needs workload evidence and operational ownership.
  3. C · Latest values are useful, but users need evidence about freshness and rebuild behavior.
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