The Data Almanac
Learn about change data capture, replication, and modern data systems.
Data Warehousing & Analytics
9 articles
- ExplainerWhat Is a Real-Time Data Warehouse? Architecture, Benefits & Use CasesLearn how real-time data warehouses use CDC and streaming ingestion to keep analytics current, plus architecture, trade-offs, and practical use cases.
- ExplainerSnowflake Schema Evolution: Managing Schema Changes in ProductionHow Snowflake schema evolution handles new columns, where native support stops, and how real-time CDC pipelines keep source and destination schemas aligned.
- ExplainerReal-Time Analytics: Architecture, Use Cases & What Makes It HardLearn real-time analytics architecture, important use cases, and why building low-latency, scalable data systems is so hard today.
- ExplainerHow Apache Iceberg Works: Catalogs, Manifests, and Snapshots ExplainedHow Apache Iceberg works: explore table formats, metadata layers, snapshots, and how Iceberg enables ACID data lakes and faster queries.
- ComparisonSnowpipe vs Snowpipe Streaming: Differences, Costs and When to Use EachSnowpipe vs Snowpipe Streaming in 2026: how each works, what Snowflake's per-GB billing means for cost, their limits on UPSERTs and schema changes, and when to use each.
- ComparisonHow to choose a data warehouseHow to choose a data warehouse. Compare Snowflake, Redshift, BigQuery, and ClickHouse by key factors.
- How-toBest Practices on Running Redshift at ScaleBest practices for running Redshift at scale. Improve performance and reduce costs with five high-impact tuning strategies.
- ExplainerSnowflake Eco ModeSnowflake Eco Mode reduces compute costs by syncing more during peak hours and scaling back off-peak.
- ExplainerWhat Are the Differences Between OLTP and OLAP Databases?OLTP vs OLAP explained: key differences, workloads, and real-world examples for transactional and analytical databases.