Blog Roll
Curated articles from datalakehousehub.com
- Latest Articles
- Migrating to Apache Iceberg: Strategies for Every Source System 2026-04-29
- Hands-On with Apache Iceberg Using Dremio Cloud 2026-04-29
- Approaches to Streaming Data into Apache Iceberg Tables 2026-04-29
- Using Apache Iceberg with Python and MPP Query Engines 2026-04-29
- Apache Iceberg Metadata Tables: Querying the Internals 2026-04-29
- Maintaining Apache Iceberg Tables: Compaction, Expiry, and Cleanup 2026-04-29
- Concurrency, Isolation, and MVCC: How Engines Handle Contention 2026-04-29
- How Data Lake Table Storage Degrades Over Time 2026-04-29
- Hash, Sort-Merge, Broadcast: How Distributed Joins Work 2026-04-29
- When Catalogs Are Embedded in Storage 2026-04-29
- Partitioning, Sharding, and Data Distribution Strategies 2026-04-29
- What Are Lakehouse Catalogs? The Role of Catalogs in Apache Iceberg 2026-04-29
- Buffer Pools, Caches, and the Memory Hierarchy 2026-04-29
- Writing to an Apache Iceberg Table: How Commits and ACID Actually Work 2026-04-29
- Volcano, Vectorized, Compiled: How Engines Execute Your Query 2026-04-29
- Hidden Partitioning: How Iceberg Eliminates Accidental Full Table Scans 2026-04-29
- Inside the Query Optimizer: How Engines Pick a Plan 2026-04-29
- Partition Evolution: Change Your Partitioning Without Rewriting Data 2026-04-29
- B-Trees, LSM Trees, and the Indexing Tradeoff Spectrum 2026-04-29
- Performance and Apache Iceberg's Metadata 2026-04-29
- How Databases Organize Data on Disk: Pages, Blocks, and File Formats 2026-04-29
- The Metadata Structure of Modern Table Formats 2026-04-29
- Row vs. Column: How Storage Layout Shapes Everything 2026-04-29
- What Are Table Formats and Why Were They Needed? 2026-04-29
- How Query Engines Think: The Tradeoffs Behind Every Data System 2026-04-29
- Agentic Analytics on the Apache Lakehouse 2026-04-13
- What is Apache Iceberg? The Table Format Revolution 2026-04-13
- What is Apache Arrow? Erasing the Serialization Tax 2026-04-13
- What is Apache Parquet? Columns, Encoding, and Performance 2026-04-13
- What is Apache Polaris? Unifying the Iceberg Ecosystem 2026-04-13
- Assembling the Apache Lakehouse: The Modular Architecture 2026-04-13
- Apache Software Foundation: History, Purpose, and Process 2026-04-13
- The Model Context Protocol (MCP) Explained: A Complete Guide to How Every Major AI Tool Connects to External Data 2026-03-07
- Context Management Strategies for VS Code with LLM Plugins: A Complete Guide to Building Your Own AI-Powered IDE 2026-03-07
- Context Management Strategies for T3 Chat: A Complete Guide to the Unified Multi-Model AI Interface 2026-03-07
- Context Management Strategies for Zed: A Complete Guide to the High-Performance AI Code Editor 2026-03-07
- Context Management Strategies for Windsurf: A Complete Guide to the AI Flow IDE 2026-03-07
- Context Management Strategies for Perplexity AI: A Complete Guide to Research-First AI Conversations 2026-03-07
- Context Management Strategies for Cursor: A Complete Guide to the AI-Native Code Editor 2026-03-07
- Context Management Strategies for OpenWork: A Complete Guide to the Desktop AI Agent Framework 2026-03-07
- Context Management Strategies for OpenCode: A Complete Guide to the Open-Source Terminal AI Agent 2026-03-07
- Context Management Strategies for Google Antigravity: A Complete Guide to the Agent-First IDE 2026-03-07
- Context Management Strategies for Gemini CLI: A Complete Guide to Terminal-Native AI Development 2026-03-07
- Context Management Strategies for Gemini Web and NotebookLM: A Complete Guide to Google's AI Knowledge Ecosystem 2026-03-07
- Context Management Strategies for Claude Code: A Complete Guide for Developers 2026-03-07
- Context Management Strategies for Claude CoWork: A Complete Guide for Knowledge Workers 2026-03-07
- Context Management Strategies for Claude Desktop: A Complete Guide to MCP, Computer Use, and Local File Access 2026-03-07
- Context Management Strategies for Claude Web: A Complete Guide to Projects, Artifacts, and Intelligent Context 2026-03-07
- Context Management Strategies for OpenAI Codex: A Complete Guide Across Browser, CLI, and App 2026-03-07
- Context Management Strategies for ChatGPT: A Complete Guide to Getting Better Results 2026-03-07
- How to Use Dremio with OpenWork: Connect, Query, and Build Data Apps 2026-03-05
- How to Use Dremio with OpenCode: Connect, Query, and Build Data Apps 2026-03-05
- How to Use Dremio with Zed: Connect, Query, and Build Data Apps 2026-03-05
- How to Use Dremio with OpenAI Codex CLI: Connect, Query, and Build Data Apps 2026-03-05
- How to Use Dremio with Amazon Kiro: Connect, Query, and Build Data Apps 2026-03-05
- How to Use Dremio with JetBrains AI Assistant: Connect, Query, and Build Data Apps 2026-03-05
- How to Use Dremio with Gemini CLI: Connect, Query, and Build Data Apps 2026-03-05
- How to Use Dremio with Google Antigravity: Connect, Query, and Build Data Apps 2026-03-05
- How to Use Dremio with Windsurf: Connect, Query, and Build Data Apps 2026-03-05
- How to Use Dremio with GitHub Copilot: Connect, Query, and Build Data Apps 2026-03-05
- How to Use Dremio with Claude CoWork: Connect, Query, and Build Data Apps 2026-03-05
- How to Use Dremio with Claude Code: Connect, Query, and Build Data Apps 2026-03-05
- How to Use Dremio with Cursor: Connect, Query, and Build Data Apps 2026-03-05
- The 2025 State of the Apache Iceberg Ecosystem Results 2026-03-01
- Connect Dremio Software to Dremio Cloud: Hybrid Federation Across Deployments 2026-03-01
- Dremio's Built-in Open Catalog: Your Zero-Configuration Apache Iceberg Lakehouse 2026-03-01
- Connect Any Iceberg REST Catalog to Dremio Cloud: Universal Lakehouse Access 2026-03-01
- Connect Databricks Unity Catalog to Dremio Cloud: Query Delta Lake Tables with Federation and AI 2026-03-01
- Connect Snowflake Open Catalog to Dremio Cloud: Multi-Engine Iceberg Analytics 2026-03-01
- Connect AWS Glue Data Catalog to Dremio Cloud: Query and Manage Your AWS Iceberg Tables 2026-03-01
- Connect Apache Druid to Dremio Cloud: Add SQL Joins, AI, and Governance to Your Real-Time Analytics 2026-03-01
- Connect MongoDB to Dremio Cloud: SQL Analytics on Document Data 2026-03-01
- Connect Vertica to Dremio Cloud: Federation for Analytics-Optimized Data 2026-03-01
- Connect Azure Synapse Analytics to Dremio Cloud: Multi-Cloud Data Warehouse Federation 2026-03-01
- Connect Snowflake to Dremio Cloud: Federate, Govern, and Accelerate Beyond Snowflake 2026-03-01
- Connect Google BigQuery to Dremio Cloud: Cross-Cloud Analytics Without Data Movement 2026-03-01
- Connect Amazon Redshift to Dremio Cloud: Extend Your Warehouse with Federation and AI Analytics 2026-03-01
- Connect Azure Storage to Dremio Cloud: Query Your Microsoft Data Lake with SQL and AI 2026-03-01
- Connect Amazon S3 to Dremio Cloud: Query Your Data Lake with SQL, Federation, and AI 2026-03-01
- Connect SAP HANA to Dremio Cloud: Unlock Analytics Beyond the SAP Ecosystem 2026-03-01
- Connect IBM Db2 to Dremio Cloud: Modernize Mainframe Analytics with Federation and AI 2026-03-01
- Connect Microsoft SQL Server to Dremio Cloud: Federate Enterprise Data Without ETL 2026-03-01
- Connect Oracle Database to Dremio Cloud: Enterprise Analytics Without Data Movement 2026-03-01
- Connect MySQL to Dremio Cloud: Federated Analytics Without ETL 2026-03-01
- Connect PostgreSQL to Dremio Cloud: Query, Federate, and Accelerate Your Data 2026-03-01
- Extract Structured Data from Text with Dremio's AI_GENERATE Function 2026-03-01
- Generate Summaries and Insights with Dremio's AI_COMPLETE Function 2026-03-01
- Classify Your Data with SQL: A Hands-On Guide to Dremio's AI_CLASSIFY Function 2026-03-01
- Semantic Layer Best Practices: 7 Mistakes to Avoid 2026-02-18
- How a Self-Documenting Semantic Layer Reduces Data Team Toil 2026-02-18
- Headless BI: How a Universal Semantic Layer Replaces Tool-Specific Models 2026-02-18
- Data Virtualization and the Semantic Layer: Query Without Copying 2026-02-18
- The Role of the Semantic Layer in Data Governance 2026-02-18
- Why Your AI Initiatives Fail Without a Semantic Layer 2026-02-18
- Semantic Layer vs. Data Catalog: Complementary, Not Competing 2026-02-18
- Semantic Layer vs. Metrics Layer: What's the Difference? 2026-02-18
- How to Build a Semantic Layer: A Step-by-Step Guide 2026-02-18
- What Is a Semantic Layer? A Complete Guide 2026-02-18
- Data Engineering Best Practices: The Complete Checklist 2026-02-18
- Pipeline Observability: Know When Things Break 2026-02-18
- Testing Data Pipelines: What to Validate and When 2026-02-18
- Partition and Organize Data for Performance 2026-02-18
- Batch vs. Streaming: Choose the Right Processing Model 2026-02-18
- Schema Evolution Without Breaking Consumers 2026-02-18
- Idempotent Pipelines: Build Once, Run Safely Forever 2026-02-18
- Data Quality Is a Pipeline Problem, Not a Dashboard Problem 2026-02-18
- How to Design Reliable Data Pipelines 2026-02-18
- How to Think Like a Data Engineer 2026-02-18
- Data Modeling Best Practices: 7 Mistakes to Avoid 2026-02-18
- Data Vault Modeling: Hubs, Links, and Satellites 2026-02-18
- Denormalization: When and Why to Flatten Your Data 2026-02-18
- Data Modeling for Analytics: Optimize for Queries, Not Transactions 2026-02-18
- Slowly Changing Dimensions: Types 1-3 with Examples 2026-02-18
- Dimensional Modeling: Facts, Dimensions, and Grains 2026-02-18
- Data Modeling for the Lakehouse: What Changes 2026-02-18
- Star Schema vs. Snowflake Schema: When to Use Each 2026-02-18
- Conceptual, Logical, and Physical Data Models Explained 2026-02-18
- What Is Data Modeling? A Complete Guide 2026-02-18
- A 2026 Introduction to Apache Iceberg 2026-02-13
- A Practical Guide to AI-Assisted Coding Tools 2026-01-15
- What Are Recursive Language Models? 2026-01-10
- RAG Isn’t a Modeling Problem. It’s a Data Engineering Problem. 2026-01-06
- Building Pangolin - My Holiday Break, an AI IDE, and a Lakehouse Catalog for the Curious 2026-01-02
- 2025 Year in Review Apache Iceberg, Polaris, Parquet, and Arrow 2025-12-29
- dremioframe & iceberg - Pythonic interfaces for Dremio and Apache Iceberg 2025-12-05
- Introducing dremioframe - A Pythonic DataFrame Interface for Dremio 2025-11-29
- Comprehensive Hands-on Walk Through of Dremio Cloud Next Gen (Hands-on with Free Trial) 2025-11-12
- 2025-2026 Guide to Learning about Apache Iceberg, Data Lakehouse & Agentic AI 2025-10-23
- An Exploration of the Commercial Iceberg Catalog Ecosystem 2025-10-21
- Building a Universal Lakehouse Catalog - Beyond Iceberg Tables 2025-10-17
- Intro to Apache Iceberg with Apache Polaris and Apache Spark 2025-10-16
- The State of Apache Iceberg v4 - October 2025 Edition 2025-10-14
- The Ultimate Guide to Open Table Formats - Iceberg, Delta Lake, Hudi, Paimon, and DuckLake 2025-09-24
- The 2025 & 2026 Ultimate Guide to the Data Lakehouse and the Data Lakehouse Ecosystem 2025-09-23
- Composable Analytics with Agents - Leveraging Virtual Datasets and the Semantic Layer 2025-09-17
- The Endgame — Building an Autonomous Optimization Pipeline for Apache Iceberg 2025-09-16
- Managing Large-Scale Optimizations — Parallelism, Checkpointing, and Fail Recovery 2025-09-09
- Unlocking the Power of Agentic AI with Apache Iceberg and Dremio 2025-09-05
- Hidden Pitfalls — Compaction and Partition Evolution in Apache Iceberg 2025-09-02
- Using Iceberg Metadata Tables to Determine When Compaction Is Needed 2025-08-26
- Designing the Ideal Cadence for Compaction and Snapshot Expiration 2025-08-19
- Avoiding Metadata Bloat with Snapshot Expiration and Rewriting Manifests 2025-08-12
- Smarter Data Layout — Sorting and Clustering Iceberg Tables 2025-08-05
- Optimizing Compaction for Streaming Workloads in Apache Iceberg 2025-07-29
- The Basics of Compaction — Bin Packing Your Data for Efficiency 2025-07-22
- The Cost of Neglect — How Apache Iceberg Tables Degrade Without Optimization 2025-07-15
- How to Discover or Organize Lakehouse & Apache Iceberg Meetups 2025-07-03
- What is an API? And Why Data Architecture Depends on Them 2025-06-23
- Decoding AWS EC2 Instance Type Names 2025-06-18
- Introduction to Data Engineering Concepts | What is Data Engineering? 2025-05-02
- Introduction to Data Engineering Concepts | Understanding Data Sources and Ingestion 2025-05-02
- Introduction to Data Engineering Concepts | ETL vs ELT – Understanding Data Pipelines 2025-05-02
- Introduction to Data Engineering Concepts | Batch Processing Fundamentals 2025-05-02
- Introduction to Data Engineering Concepts | Streaming Data Fundamentals 2025-05-02
- Introduction to Data Engineering Concepts | Data Modeling Basics 2025-05-02
- Introduction to Data Engineering Concepts | Data Warehousing Fundamentals 2025-05-02
- Introduction to Data Engineering Concepts | Data Lakes Explained 2025-05-02
- Introduction to Data Engineering Concepts | Storage Formats and Compression 2025-05-02
- Introduction to Data Engineering Concepts | Data Quality and Validation 2025-05-02
- Introduction to Data Engineering Concepts | Metadata, Lineage, and Governance 2025-05-02
- Introduction to Data Engineering Concepts | Scheduling and Workflow Orchestration 2025-05-02
- Introduction to Data Engineering Concepts | Building Scalable Pipelines 2025-05-02
- Introduction to Data Engineering Concepts | Cloud Data Platforms and the Modern Stack 2025-05-02
- Introduction to Data Engineering Concepts | DevOps for Data Engineering 2025-05-02
- Introduction to Data Engineering Concepts | Data Lakehouse Architecture Explained 2025-05-02
- Introduction to Data Engineering Concepts | Apache Iceberg, Arrow, and Polaris 2025-05-02
- Introduction to Data Engineering Concepts | The Power of Dremio in the Modern Lakehouse 2025-05-02
- A Journey from AI to LLMs and MCP - 10 - Sampling and Prompts in MCP — Making Agent Workflows Smarter and Safer 2025-04-14
- A Journey from AI to LLMs and MCP - 9 - Tools in MCP — Giving LLMs the Power to Act 2025-04-13
- A Journey from AI to LLMs and MCP - 8 - Resources in MCP — Serving Relevant Data Securely to LLMs 2025-04-12
- A Journey from AI to LLMs and MCP - 7 - Under the Hood — The Architecture of MCP and Its Core Components 2025-04-11
- Journey from AI to LLMs and MCP - 6 - Enter the Model Context Protocol (MCP) — The Interoperability Layer for AI Agents 2025-04-10
- A Journey from AI to LLMs and MCP - 5 - AI Agent Frameworks — Benefits and Limitations 2025-04-09
- A Journey from AI to LLMs and MCP - 4 - What Are AI Agents — And Why They're the Future of LLM Applications 2025-04-08
- A Journey from AI to LLMs and MCP - 3 - Boosting LLM Performance — Fine-Tuning, Prompt Engineering, and RAG 2025-04-07
- A Journey from AI to LLMs and MCP - 2 - How LLMs Work — Embeddings, Vectors, and Context Windows 2025-04-06
- A Journey from AI to LLMs and MCP - 1 - What Is AI and How It Evolved Into LLMs 2025-04-05
- Building a Basic MCP Server with Python 2025-04-04
- Using Helm with Kubernetes - A Guide to Helm Charts and Their Implementation 2025-02-19
- Crash Course on Developing AI Applications with LangChain 2025-02-01
- The Data Lakehouse - The Benefits and Enhancing Implementation 2025-01-31
- 2025 Comprehensive Guide to Apache Iceberg 2025-01-20
- When to use Apache Xtable or Delta Lake Uniform for Data Lakehouse Interoperability 2025-01-07
- 2025 Guide to Architecting an Iceberg Lakehouse 2024-12-09
- 10 Future Apache Iceberg Developments to Look forward to in 2025 2024-11-25
- Deep Dive into Dremio's File-based Auto Ingestion into Apache Iceberg Tables 2024-11-15
- Intro to SQL using Apache Iceberg and Dremio 2024-11-08
- Dremio, Apache Iceberg and their role in AI-Ready Data 2024-11-05
- Introduction to Cargo and cargo.toml 2024-11-05
- Leveraging Python's Pattern Matching and Comprehensions for Data Analytics 2024-11-01
- Hands-on with Apache Iceberg & Dremio on Your Laptop within 10 Minutes 2024-10-31
- Data Modeling - Entities and Events 2024-10-30
- All About Parquet Part 01 - An Introduction 2024-10-21
- All About Parquet Part 02 - Parquet's Columnar Storage Model 2024-10-21
- All About Parquet Part 03 - Parquet File Structure | Pages, Row Groups, and Columns 2024-10-21
- All About Parquet Part 04 - Schema Evolution in Parquet 2024-10-21
- All About Parquet Part 05 - Compression Techniques in Parquet 2024-10-21
- All About Parquet Part 06 - Encoding in Parquet | Optimizing for Storage 2024-10-21
- All About Parquet Part 07 - Metadata in Parquet | Improving Data Efficiency 2024-10-21
- All About Parquet Part 08 - Reading and Writing Parquet Files in Python 2024-10-21
- All About Parquet Part 09 - Parquet in Data Lake Architectures 2024-10-21
- All About Parquet Part 10 - Performance Tuning and Best Practices with Parquet 2024-10-21
- Orchestrating Airflow DAGs with GitHub Actions - A Lightweight Approach to Data Curation Across Spark, Dremio, and Snowflake 2024-10-19
- A Deep Dive Into GitHub Actions From Software Development to Data Engineering 2024-10-19
- A Guide to dbt Macros - Purpose, Benefits, and Usage 2024-10-18
- Data Lakehouse Roundup 1 - News and Insights on the Lakehouse 2024-10-16
- Getting Started with Data Analytics Using PyArrow in Python 2024-10-15
- What is Three-Tier Data (Bronze, Silver, Gold) and How Dremio Simplifies It 2024-10-09
- A Brief Guide to the Governance of Apache Iceberg Tables 2024-10-07
- Exploring Data Operations with PySpark, Pandas, DuckDB, Polars, and DataFusion in a Python Notebook 2024-10-07
- Ultimate Directory of Apache Iceberg Resources 2024-10-05
- Change Data Capture (CDC) when there is no CDC 2024-10-04
- Virtualization + Lakehouse + Mesh = Data At Scale 2024-09-25
- Deep Dive into Data Apps with Streamlit 2024-09-22
- A Deep Dive into Docker Compose 2024-09-21
- Hands-on with Apache Iceberg on Your Laptop - Deep Dive with Apache Spark, Nessie, Minio, Dremio, Polars and Seaborn 2024-09-12
- Why Data Analysts, Engineers, Architects and Scientists Should Care about Dremio and Apache Iceberg 2024-09-10
- 5 Trends in the Data Lakehouse Space 2024-09-01
- Using the alexmerced/datanotebook Docker Image 2024-08-30
- Understanding Apache Iceberg Delete Files 2024-08-29
- Understanding the Apache Iceberg Manifest 2024-08-27
- Understanding the Apache Iceberg Manifest List (Snapshot) 2024-08-25
- Understanding Apache Iceberg's Metadata.json 2024-08-21
- What Apache Iceberg REST Catalog is and isn't 2024-08-18
- ACID Guarantees and Apache Iceberg - Turning Any Storage into a Data Warehouse 2024-08-15
- Data Lakehouse 101 - The Who, What and Why of Data Lakehouses 2024-08-05
- Understanding the Polaris Iceberg Catalog and Its Architecture 2024-07-31
- Apache Iceberg Reliability 2024-07-26
- Upcoming Data Talks from Alex Merced (And how to follow) 2024-07-20
- Databases Deconstructed - The Value of Data Lakehouses and Table Formats 2024-07-12
- Video Course - Basics of Lakehouse Engineering - Apache Iceberg, Nessie, Dremio 2024-06-26
- Partitioning with Apache Iceberg - A Deep Dive 2024-05-29
- 3 Reasons Data Engineers Should Embrace Apache Iceberg 2024-05-15
- Running SQL on your Excel Files From Your Laptop with Dremio 2024-05-03
- Understanding the Future of Apache Iceberg Catalogs 2024-04-04
- A Deep Intro to Apache Iceberg and Resources for Learning More 2024-04-04
- End-to-End Basic Data Engineering Tutorial (Spark, Dremio, Superset) 2024-04-01
- 5 Open Source Data Projects You Should Be Following 2024-03-19
- 5 Reasons Dremio is the Ideal Apache Iceberg Lakehouse Platform 2024-03-09
- The Apache Iceberg Lakehouse - The Great Data Equalizer 2024-03-06
- 10 Reasons to Make Apache Iceberg and Dremio Part of Your Data Lakehouse Strategy 2024-03-01
- A deep dive into the concept and world of Apache Iceberg Catalogs 2024-03-01
- Introduction to ANSI SQL - Understanding the Syntax and Concepts 2024-02-24
- The Role of Ontologies in Data Management 2024-02-24
- What is the Data Lakehouse and the Role of Apache Iceberg, Nessie and Dremio? 2024-02-21
- Partitioning Practices in Apache Hive and Apache Iceberg 2024-02-12
- Columnar vs. Row-based Data Structures in OLTP and OLAP Systems 2024-02-03
- Introduction to Data Vault Modeling 2024-02-02
- Table Format FUD - Thinking Through the Table Format Conversion (Apache Iceberg, Apache Hudi, Delta Lake) 2024-02-02
- Embracing the Future of Data Management - Why Choose Lakehouse, Iceberg, and Dremio? 2024-01-25
- Open Lakehouse Engineering/Apache Iceberg Lakehouse Engineering - A Directory of Resources 2024-01-19
- Nessie - An Alternative to Hive & JDBC for Self-Managed Apache Iceberg Catalogs 2024-01-08
- Apache Iceberg, Git-Like Catalog Versioning and Data Lakehouse Management - Pillars of a Robust Data Lakehouse Platform 2024-01-03
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