Data storage for modern applications - Mike Lehan
summary
Practical guidance on when to swap SQL for other stores and how to migrate: document examples use MongoDB documents and projections, cache and broker examples use Redis with disk persistence and TTLs, and wide‑scale key/value use recommends DynamoDB on‑demand (0→3,000 r/s, scales toward 40k; beware cost per secondary index). ETL patterns push data into ElasticSearch or Snowflake for analytics, and a ledger (QLDB) is used for financial history with daily hash exports to Slack to verify immutability.
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chapters (16)
- 0:00Introduction
- 0:54Overview
- 1:13Relational Data
- 2:21Clarification
- 3:23Principles
- 7:20New Tables
- 9:12Structured Data
- 12:25Key Value Stores
- 14:55Amazon Dynamo DB
- 20:20Portability of storage
- 22:38Serverless databases
- 24:47Extract transform and load
- 27:26Elastic search
- 35:31Queues
- 38:02SQS
- 41:52Summary
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