Bean & Bark: learn DynamoDB by doing

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Meet Bean & Bark — a coffee roaster whose entire store lives in one DynamoDB table. You're the new hire. Across four short chapters a real problem lands on your desk each time, and you solve it with a query — learning DynamoDB by doing, on a dataset with actual stories hidden in it.

This isn't a syllabus of features. Each chapter is a situation: the founder needs an answer before a meeting, a region's revenue has slipped, a cleanup has to run against live data, a standing report needs its own key. You write the query, and the studio shows you exactly what it costs and what it would change — the same disclosure you'd rely on for real work.

Everything here runs against your own DynamoDB — a local one on your laptop is ideal: free, offline, nothing to provision. No AWS account required to follow along. Start at the top and use the Next button, or jump to the job you have right now:

Answer the founder
Find one customer’s orders in a single cheap read — and learn to tell a Query from a Scan by watching what each one costs.
Break down a drop
Explain a 12% revenue dip with SUM and GROUP BY, and feel what a cross-cutting business question actually costs.
Change prod without fear
Edit production data behind a preview and a backup, so a wrong WHERE clause is a shrug on screen, not lost data.
Index a new question
When the partition key can’t answer a standing question — every order in the fulfillment queue — add a GSI and turn a whole-table Scan into a cheap Query.
Set up
  • Bean & Bark sample dataset The seed for this whole series — ~5,900 items in DynamoDB-JSON. Import it into DynoStudio, or load it into DynamoDB Local; the README and one-command seed script sit alongside it under /datasets/bean-and-bark/.
  • Run DynamoDB Local AWS docs: run DynamoDB on your own machine — free, offline, nothing to provision.
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