Tag:data lakehouse
Articles tagged "data lakehouse".
- 9 MIN READ•Oct 21, 2024
Parquet Metadata Explained: Footer, Row Groups, Statistics
Parquet metadata lives in the file footer: the schema, row group layout and per-column min/max statistics that let query engines skip data they do not need.
data lakehousedata engineeringapache parquet - 7 MIN READ•Oct 21, 2024
Read and Write Parquet Files in Python (PyArrow, Pandas)
How to read and write Parquet files in Python with PyArrow, FastParquet, and Pandas, including column selection, compression, and partitioned datasets.
data lakehousedata engineeringapache parquet - 9 MIN READ•Oct 21, 2024
Parquet Performance Tuning: 8 Best Practices
Tune Apache Parquet for speed and cost: row group and file sizes, partitioning, Snappy vs ZSTD compression, encodings, sorting, and predicate pushdown.
data lakehousedata engineeringapache parquet - 43 MIN READ•Sep 23, 2025
Data Lakehouse Guide 2026: Architecture and Ecosystem
What a data lakehouse is and how it works: Iceberg, Delta, Hudi, and Paimon table formats, the five core layers, catalogs, ingestion, and optimization.
Data LakehouseData EngineeringAgentic AI - 23 MIN READ•Sep 24, 2025
Open Table Formats Compared: Iceberg, Delta, Hudi, Paimon
Apache Iceberg, Delta Lake, Hudi, Paimon and DuckLake compared: metadata design, row-level updates, engine support, and when to choose each table format.
Data LakehouseData EngineeringAgentic AI - 6 MIN READ•Feb 18, 2026
What Is Data Modeling? Definition, Types, and Examples
Data modeling defines the entities, attributes, and relationships in your data. Learn the conceptual, logical, and physical levels and the main techniques.
data modelingdata engineeringdata lakehouse - 6 MIN READ•Feb 18, 2026
What Is a Semantic Layer? Definition, Parts, and Examples
A semantic layer maps raw tables and columns to business terms and metrics so every BI tool and AI agent gets the same answer. Learn what it contains.
semantic layerdata engineeringdata lakehouse - 20 MIN READ•Aug 4, 2026
Autonomous Table Optimization When Your Query Workload Stops Being Predictable
Autonomous table optimization when query workloads stop being predictable: observing file layout and query patterns, scoring compaction work, adaptive.
Apache IcebergTable OptimizationCompaction - 21 MIN READ•Aug 4, 2026
Reading the Apache Iceberg V4 Proposals Before They Land
A field guide to the Apache Iceberg V4 proposals: adaptive metadata trees, single-file commits, typed statistics, column families, and what is safe.
Apache IcebergIceberg V4Metadata - 21 MIN READ•Aug 4, 2026
Building an Honest TCO Model for Open Lakehouses and Proprietary Warehouses
An honest TCO framework for open lakehouses versus proprietary warehouses: five cost categories, measured numbers, sensitivity analysis, and where each.
TCOData LakehouseData Warehouse - 21 MIN READ•Aug 4, 2026
How the Iceberg REST Catalog Turned Into the Lakehouse Control Plane
How the Iceberg REST catalog became the lakehouse control plane: multi-table atomic commits, credential vending, capability negotiation, and what still breaks.
Apache IcebergREST CatalogApache Polaris - 20 MIN READ•Aug 4, 2026
A Migration Playbook for Moving Legacy Warehouses onto Apache Iceberg
A dependency-first playbook for migrating legacy warehouses onto Apache Iceberg: snapshot vs migrate vs add_files, four-level parity validation.
Apache IcebergMigrationData Warehouse