How Data Caching Works in Unifier

Review the following information to learn more about the benefits of data caching.

What is caching?

Caching is a performance optimization technique where system-generated query results are stored temporarily, so users can access data faster without running live queries every time.

How can it be enabled in Unifier data sources?

In Unifier, caching helps improve the responsiveness of visualizations that are based on Business Process (BP) records. Enabling caching for Business Process data sources will improve performance and reduce the load on real-time data retrieval.

Caching allows users to quickly access data for visualizations without waiting for live queries to run every time, making visualization content more responsive and user-friendly.

Note: Caching is available only for Business Process data sources. Data views will not have caching enabled.

Why is caching provided or why enable caching?

It is recommended to enable caching to:

Improve performance of visualizations by reducing query time
Minimize system load and avoid unnecessary real-time queries for data that does not frequently change
Provide faster user experience for content that is reviewed periodically rather than in real-time

How does caching work?

When caching is enabled for a data source, Unifier temporarily stores query results. When a visualization requests the same data, Unifier retrieves it from cache instead of re-executing the query.

How often is cached data refreshed?

Cached data is automatically refreshed every 4 hours after cache creation. Cache is created when a data source is published. This refresh ensures data is relatively current while optimizing performance.

Note: Based on system load , available resources and number of caches being refreshed or created in parallel, the exact time of refresh could be few minutes more from the scheduled 4 hours.

Benefits of caching

Faster load times for dashboards and visualizations
Reduced system load from frequent or repetitive queries
Better user experience for content that does not require real-time updates

When to use cached data?

Caching is ideal for visualizations where:

Data does not change frequently (for example, daily/weekly reviews)
Content used to track overall trends or statuses, not real-time activities
Users want quick access high-level data without waiting for live refresh.(periodical)

Examples of good use cases for cached data:

Monthly or weekly project status dashboards
Reports on cumulative transactions or approvals

Why is caching provided or why enable caching?

See Also