Topic
Modern Warehouse Platforms
Snowflake, BigQuery, Redshift, Databricks, and the platform-level trade-offs that shape how a warehouse is built on top of them.
12 entries
Techniques
2
Technique
Data virtualization: federated query in modern stacks
How data virtualization works as a technique, what it shares with and how it differs from federated query and the logical data warehouse, where it fits in cloud warehouse stacks, and the failure modes that determine when virtualization holds up in production.
Read →Technique
Logical data warehouse: the architectural pattern
The logical data warehouse unifies a physical warehouse with lakehouses, operational stores, and SaaS sources behind a single query layer. How the pattern actually works in 2026, where it fits, and where it quietly breaks.
Read →
Comparisons
2
Comparison
Data warehouse vs data lake vs data mart vs lakehouse
Data warehouse vs data lake vs data mart vs lakehouse: four distinct architectural commitments, what each one actually is, how they compare on storage, governance, query engine, and workload, and when each is the right choice in a 2026 stack.
Read →Comparison
ETL vs ELT
ETL vs ELT: what the order of operations actually changes, why cloud columnar warehouses shifted the default from ETL to ELT, the trade-offs that determine which pattern fits a given workload, and a note on where reverse ETL fits.
Read →
Glossary
6
Glossary
Apache Iceberg
An open table format that adds a metadata layer over data files (typically Parquet) in object storage, giving lake data ACID transactions, schema and partition evolution, and time-travel queries any compatible engine can read.
Read →Glossary
BigQuery
Google Cloud's serverless, columnar data warehouse, in which storage and compute are fully decoupled and queries run on an automatically provisioned pool of resources billed by data scanned or by reserved capacity.
Read →Glossary
Data lakehouse
Object storage plus an open table format (Iceberg, Delta, or Hudi), exposing lake-style data through a warehouse-style table abstraction with ACID, schema enforcement, and time travel.
Read →Glossary
Delta Lake
An open table format, originated by Databricks, that adds a transaction log over Parquet files in object storage to give lake data ACID transactions, time travel, and schema enforcement under a warehouse-style table abstraction.
Read →Glossary
Redshift
Amazon Web Services' columnar, massively parallel (MPP) data warehouse; RA3 node types and a serverless option separate compute from managed storage, with deep integration into the AWS analytics stack.
Read →Glossary
Snowflake
A cloud data warehouse with a multi-cluster, shared-data architecture that separates storage from compute, letting independent compute clusters query one copy of the data; available on AWS, Azure, and Google Cloud.
Read →