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Data warehouses help businesses analyze large amounts of data for better decision-making.

Data lakes store large volumes of diverse data for analytics and processing.

Data Lakehouse architecture merges flexible data storage with reliable analytics capabilities.

Change Data Capture allows real-time syncing of database changes to other systems.

Downsampling and aggregation reduce data volume while preserving essential trends.

CDC with Kafka allows real-time updates from databases to multiple services.

Time-series databases are designed to store and query time-stamped metrics efficiently.

OLTP handles transactions while OLAP is for data analysis and reporting.