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.
The Agent Is Now a Named Coworker, and It Needs a File Format
Named, persistent agents need a file format. Open Agent Profile, Buzz, Grok Bot, and Hermes Bot Mode show why a portable agent identity matters.
Read Article →Your Agent Should Answer the Phone: A Field Guide to AI Gateways on Slack, Discord, Telegram, Signal, and Teams
A field guide to AI gateways on Slack, Discord, Telegram, Signal, and Teams: architecture, auth, cost, and the failure modes that matter.
Read Article →Graphs in AI Engineering Have Solved Three Problems. The Fourth Is the Plan.
Knowledge graphs, GraphRAG, and LangGraph solved three problems. The fourth is the work itself: a reviewable graph of bounded agentic loops.
Read Article →The Hidden Cost of Tiny Iceberg Commits
Trace what one tiny Iceberg commit writes, then model hourly, per-minute, and per-second cadences so streaming costs become arithmetic, not adjectives.
Read Article →Deletion Vectors vs Position Deletes vs Equality Deletes: The Iceberg Delete Story in 2026
Position deletes, equality deletes, and deletion vectors compared from the Iceberg spec: what each writes, how readers apply it, and when to use which.
Read Article →Iceberg Is Becoming a Library, Not Just a Table Format
Iceberg is turning from a JVM table format into a library other systems embed. What that shift changes for engines, catalogs, and the spec itself.
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