Panel Discussion
summary
Panelists argue concrete tradeoffs: EDB claims it contributes over 30% of Postgres code annually, Postgres remains a solid default but not ideal for >10TB analytics, and teams are using DuckDB in thousands of Lambda jobs for ETL to cut costs. A sharing feature is described as a share URL snapshot that other services can attach. Discussion highlights the pendulum back to explicit data modeling, pressure for simpler stacks, finOps-driven cost scrutiny, and the unresolved need for federated computational governance.
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chapters (12)
- 0:00Introduction
- 1:05Panelists introduce
- 2:28Why different databases
- 5:40Database evolution
- 7:25Structured data modeling
- 10:12Data modeling simplicity
- 15:09Audience questions on database types and modeling
- 21:52Data mesh vs schemas
- 26:53Data mesh in practice
- 28:16Data product modeling
- 32:10Trends for data engineers
- 39:54Closing
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