The data platform reading list, autumn 2026
Snowflake and Databricks shipped six long guides between them this quarter. Here is who should read which.
If you build pipelines
Databricks' Big Book of Data Engineering is in its fourth edition: ETL scaling patterns, orchestration, observability, and real code. It is long. Start with observability.
If someone asked you about Postgres for agents
Lakebase For Dummies explains Databricks' serverless Postgres, with storage split from compute so you can branch a database like code and scale it to zero. The For Dummies format suits a new category.
If your org chart is the bottleneck
How to Knit Your Data Mesh on Snowflake. Data mesh is an organizational idea before it is a technical one, and this paper starts with the domain teams before it gets to the platform.
If legal keeps blocking data sharing
The Essential Guide to Data Sharing covers live sharing without copies, marketplaces, and governance.
If you are building an app on the warehouse
7 Snowflake Reference Architectures for Application Builders has seven use cases with design patterns you can steal.
If you need to make the case upstairs
Data Strategies for AI Leaders, the MIT Technology Review Insights survey of more than 275 leaders. Four in five businesses, it found, aren't ready for generative AI because of their data foundations. That sentence tends to end budget meetings well.