5 articles
Analyze petabyte-scale datasets with Google BigQuery: SQL querying, cost optimization, partitioning, clustering, data loading, and integration with the GCP data stack for engineers and analysts.
Build a comprehensive analytics backend for AI features. Track queries, user satisfaction, funnel conversion, and detect anomalies in AI system behavior.
ClickHouse is a columnar database that ingests millions of rows per second. Learn when it beats PostgreSQL, MergeTree engines, and how to integrate it with your Node.js stack.
Master ClickHouse for analytics: MergeTree engines, materialized views, CDC from Postgres, dual-write patterns, and query optimization.
Master TimescaleDB hypertables, continuous aggregates, compression, retention policies, and time-bucketing for sub-second time-series queries.