Optimizing complex data manipulations using in-database analytics
Following Spotfire 5.0, it has been possible to push data calculations and aggregations to the source system, facilitating the handling of data volumes too large to fit into the primary memory and take advantage of the power of the source database. When using this in-database (in-db) analytic functionality, you access only a selected or aggregated set of data.
When a visualization is configured to use an in-db connection, every time a change is made to the visualization's data-dependent properties, a new query is sent to the external data source and a new table of aggregated data is returned.
The use of in-db data, as opposed to in-memory data, does introduce limitations. For example, ...
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