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.
Mastering Apache Iceberg v3 Deletion Vectors for High-Throughput Streaming Ingest
Apache Iceberg v3 deletion vectors for high-throughput streaming ingest: how bitmaps and Puffin files fix CDC write amplification and read decay.
Read Article →The Decoupled Data Lakehouse: Multi-Engine Freedom with Open REST Catalogs
The decoupled data lakehouse: multi-engine freedom with open REST catalogs, credential vending, and an estate that outlives its tools.
Read Article →The Five Layers of an Agentic Lakehouse
The five layers of an agentic lakehouse: Storage, Catalog, Semantic, Gateway, and Agent Surface, and how one question travels through all of them.
Read Article →Goal-Directed Data Quality Agents: Anomaly Quarantine on Apache Iceberg
Goal-directed data quality agents that watch Apache Iceberg tables, detect anomalies, and quarantine suspect data safely with snapshot isolation and branches.
Read Article →Managing the TCO of Agentic Analytics: Token Budgets, Query Throttles, and the Economics of Autonomy
Managing the total cost of agentic analytics: token budgets, query throttles, unit economics, and the FinOps discipline that keeps AI spend under control.
Read Article →Metric Contracts in 2026: Standardizing Business Logic Across Multi-Agent Frameworks
Metric contracts in 2026: versioned, testable definitions of business logic that let multi-agent frameworks compute revenue identically, with OSI interchange.
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