Insights

In-depth, practical guides to AWS and Databricks data engineering: architecture, pipelines, governance, streaming, cost and AI.

LatestAWS + Databricks

Databricks on AWS: 9 Proven Steps to a Secure Lakehouse

A 2026 reference architecture for Databricks on AWS: workspaces, serverless vs classic compute, PrivateLink, S3 and Unity Catalog, KMS, identity, cost and DR.

October 25, 2026 15 min read

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AWS data lake architecture diagram with ingestion, S3 and Iceberg storage, Glue Data Catalog, Lake Formation and analytics

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AWS Data Engineering

AWS Data Lake Architecture: 7 Reliable Layers That Scale

A 2026 layer-by-layer guide to AWS data lakes: ingestion, S3 Tables and Iceberg, Glue Data Catalog, Glue 6.0 and EMR, Lake Formation, consumption and cost.

Publishing November 1, 2026

Unity Catalog best practices diagram showing metastore, catalogs, schemas, managed tables and ABAC policies

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Databricks Lakehouse

Unity Catalog Best Practices: 12 Proven Rules for Governance

Twelve opinionated Unity Catalog rules for 2026, from metastore and catalog layout to managed tables, ABAC policies, system-table audits and hive_metastore migration.

Publishing November 10, 2026

AWS Glue vs Databricks comparison of Spark runtime, pricing model, catalog and orchestration

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AWS + Databricks

AWS Glue vs Databricks: 8 Honest Differences for 2026

An honest 2026 comparison of AWS Glue 6.0 and Databricks: runtime, pricing, developer experience, governance, formats, streaming, ML and when to use both.

Publishing November 17, 2026