infrastructure

Data Warehouse

A data warehouse is an analytical database optimised for querying and reporting on large volumes of structured historical data aggregated from multiple sources including web scraping.

Data warehouses (Snowflake, BigQuery, Redshift, ClickHouse) are designed for OLAP (Online Analytical Processing) — complex aggregations over billions of rows — rather than OLTP (transactional reads and writes). They use columnar storage, which compresses repeated values efficiently and enables fast full-column scans for aggregation queries.

For scraping pipelines, the data warehouse is the analytical destination: cleaned, normalised, and deduplicated scraped records are loaded via batch ETL or streaming (via Kafka/BigQuery Streaming Inserts) into fact and dimension tables. Analysts then query the warehouse with SQL to answer business questions — price trend analysis, competitor monitoring, market share estimation.

BigQuery and Snowflake both support external tables over data lake storage (S3, GCS), allowing semi-structured JSON scraped data to be queried without pre-defining a schema — combining the flexibility of a data lake with the query capability of a warehouse.

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    Data Warehouse — Web Scraping Glossary | AlterLab