Data engineering is entering its most transformative era yet-and data virtualization is now at the center of every modern architecture.
As organizations scale across warehouses, lakehouses, streaming systems, and multicloud environments, the ability to query data without moving it has become a mission-critical engineering capability.
Data Virtualization for Engineers is the definitive, up-to-date 2025 guide for building high-performance logical data platforms using Trino, Dremio, Denodo, DuckDB Fusion, Iceberg, Delta Lake, Kafka, Redpanda, and Arrow Flight. Designed for engineers, architects, and platform teams, this book provides real-world patterns, hands-on labs, and production-grade blueprints that unify your entire data ecosystem into a single federated layer.
You will learn exactly how to:
→ Build distributed SQL engines that join S3, PostgreSQL, BigQuery, and Snowflake without ETL
→ Virtualize Iceberg, Delta, Parquet, relational DBs, streaming topics, APIs, and SaaS systems
→ Scale Trino coordinators, tune CBO pushdown, configure high-performance catalogs, and optimize cross-source joins
→ Accelerate lakehouse analytics with Dremio Reflections, Arrow columnar execution, and Gandiva acceleration
→ Deploy enterprise virtualization with Denodo's semantic layer, governance controls, data masking, and MPP caching
→ Build lightweight, local, and edge-powered engines with DuckDB Fusion and Polars for LLM workloads and BI acceleration
→ Integrate streaming systems with Kafka, Redpanda, and Pulsar for real-time federated analytics
→ Apply security, lineage, access policies, masking, RBAC/ABAC, and enterprise-wide governance
→ Deploy full virtualization stacks using Docker, Kubernetes, Terraform, and IaC-driven pipelines
Every chapter includes a fully reproducible practice lab, culminating in a complete End-to-End Production Virtualization Platform built on Trino + Dremio + Denodo + DuckDB Fusion with multicloud, streaming, lakehouse, and governance components.
By the end of this book, you will be able to design, deploy, and operate modern logical architectures that deliver consistent, secure, real-time access to data-across every system in your organization-without duplication, delays, or complexity.
This is the most complete, modern, and engineering-oriented guide to data virtualization available today.
Perfect for data engineers, architects, platform teams, analytics engineers, and anyone building next-generation data ecosystems.
