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

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

Downsampling and aggregation reduce data volume while preserving essential trends.

Replicas keep your system available, while snapshots allow for data recovery.

Deep pagination in Elasticsearch can slow down searches significantly, but there are efficient methods to handle it.

API pagination helps manage large datasets by breaking them into smaller parts.

Elasticsearch aggregations help analyze data by grouping, calculating, and estimating values.

Cache breakdowns can overwhelm databases, but request coalescing solves this issue.