Caching Overview

Learn how Cube’s caching layer accelerates queries with pre-aggregations.

Caching

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

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.

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

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.

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