Developer Education Hub
Tutorials for developers who read the source.
Written by Alex Merced, Head of Developer Relations at Dremio and author of 35+ books.
Guides on web development, data engineering, Apache Iceberg, and agentic AI. Guest submissions are welcome. Pitch an idea at alex@grokoverflow.com.
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Must Reads — Data Lakehouses & Agentic Analytics
Authoritative guides from the Dremio blog on building intelligent, open lakehouse architectures.
The Semantic Layer: The Definitive Guide
Understand how a semantic layer unifies business logic, accelerates self-service analytics, and becomes the foundation of AI-ready data architectures.
Read on Dremio.com →Apache PolarisApache Polaris: The Catalog Standard for Lakehouses and AI
Learn how Apache Polaris is establishing a universal open catalog standard that lets any engine read and write Apache Iceberg tables without vendor lock-in.
Read on Dremio.com →Table FormatsWhat Are Table Formats and Why Were They Needed?
Trace the evolution from raw Parquet files to modern table formats like Apache Iceberg — the innovation that unlocked ACID transactions on object storage.
Read on Dremio.com →DremioWhat Is Dremio?
A comprehensive overview of Dremio's Intelligent Lakehouse Platform — how reflections, semantic layers, and multi-engine federation work together.
Read on Dremio.com →Apache IcebergWhat Apache Iceberg Native Actually Means
Cut through the marketing: discover what it truly means to be Apache Iceberg-native versus merely Iceberg-compatible, and why the distinction matters.
Read on Dremio.com →Open SourceOpen Source and the Data Lakehouse
Explore how open-source projects — Iceberg, Parquet, Arrow, and Polaris — form an interoperable stack that keeps your data free from proprietary control.
Read on Dremio.com →Agentic AIWhat Is Agentic Analytics?
Discover how AI agents autonomously query, reason over, and act on lakehouse data — fundamentally changing how organizations derive insight at scale.
Read on Dremio.com →LakehouseThe Definitive Guide to the Data Lakehouse
The canonical end-to-end guide: what a data lakehouse is, how it compares to data warehouses and data lakes, and how to architect one for your organization.
Read on Dremio.com →PerformanceHow Dremio Keeps Agentic Analytics Fast Without Manual Tuning
Learn how Dremio's autonomous optimization layer — reflections, compaction, and vectorized execution — keeps AI agent queries fast without manual DBA work.
Read on Dremio.com →Recent Articles & Tutorials
Stay up to date with my latest guides, walkthroughs, and deep dives on data lakehouses, web development, and AI.
Data Quality Tooling Compared: Great Expectations, Soda, dbt Tests, and Anomaly Detection
A comparison of Great Expectations, Soda, dbt tests, and anomaly detection, and a layered design that uses each where it fits.
Read Article →The Data Team of the Agentic Era: Generalists Owning End-to-End Workflows
The case for generalists owning end-to-end data workflows with agents, the counterargument, and how to make the transition work.
Read Article →dbt on Iceberg: Incremental Models on Open Tables
How dbt incremental materializations map to Iceberg operations, and the configuration, predicates, and maintenance that keep them healthy.
Read Article →Disaster Recovery for Iceberg Tables: Replication, Backup, and Restore
Disaster recovery for Iceberg across four tiers: snapshots, object versioning, catalog backup, and cross-region replication.
Read Article →Deleting User Data From an Immutable Lakehouse: GDPR Hard Deletes on Iceberg
How to turn a logical delete on immutable Iceberg into a physical erasure across snapshots, versions, replicas, and downstream copies.
Read Article →Geospatial Data in Apache Iceberg: Geometry, Geography, and GeoParquet
How Iceberg v3 geometry and geography types, bounding boxes, and native Parquet types give spatial data first-class standing.
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