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Caching Cube provides a powerful caching layer through pre-aggregations — materialized rollup tables that dramatically accelerate query performance and reduce data warehouse costs.

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How it works

1

Define pre-aggregations

Specify rollup tables in your data model with the measures and dimensions to cache.
2

Cube builds the cache

Cube queries your data warehouse and stores results in Cube Store, a purpose-built caching engine.
3

Queries are served from cache

When a query matches a pre-aggregation, Cube serves it from the cache instead of hitting the warehouse.
4

Automatic refresh

Pre-aggregations are refreshed on a configurable schedule to keep data fresh.

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Defining pre-aggregations

Add pre-aggregations to your cube definitions: 
cubes:
  - name: orders
    # ... measures and dimensions ...

    pre_aggregations:
      - name: orders_by_day
        measures:
          - count
          - total_amount
        dimensions:
          - status
        time_dimension: created_at
        granularity: day

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Refresh strategy

Control how often pre-aggregations are rebuilt: 
pre_aggregations:
  - name: orders_by_day
    measures:
      - count
    time_dimension: created_at
    granularity: day
    refresh_key:
      every: "1 hour"
Setting very frequent refresh intervals can increase your data warehouse costs. Balance freshness with cost.

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Benefits

  • 10-100x faster queries compared to hitting the warehouse directly
  • Reduced warehouse costs by minimizing direct queries
  • Consistent performance regardless of data volume
  • Automatic query routing — no changes needed in your application code