Snowflake versus In-memory Features: Difference between revisions
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|style="text-align:center;"|X | |style="text-align:center;"|X | ||
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|| | ||Conformance analysis using BPMN design models | ||
|style="text-align:center;"|X | |style="text-align:center;"|X | ||
||Planned in PA 2023.3 | ||Planned in PA 2023.3 | ||
|- | |- | ||
|| | ||Statistical aggregations (median, percentile, standard deviation, variance) | ||
|style="text-align:center;"|X | |style="text-align:center;"|X | ||
||Planned in PA 2023.3 | ||Planned in PA 2023.3 | ||
Revision as of 10:42, 18 April 2023
This page describes differences in available features between in-memory and Snowflake dashboards.
| Feature | In-memory | Snowflake |
|---|---|---|
| Event filtering based on event attributes and expressions (by any criteria) | Only by event types | X |
| Filter rules can be defined for measures and dimensions | X | |
| Dynamic event type mapping (allows to set event type for each chart/flowchart) | X | |
| Conformance analysis using BPMN design models | X | Planned in PA 2023.3 |
| Statistical aggregations (median, percentile, standard deviation, variance) | X | Planned in PA 2023.3 |
| Root causes analysis for flowchart | X | Planned in PA 2023.3 |
| Calculated attributes to create reusable measures | X | Planned in PA 2023.4 |
| Notifications and alerts to initiate corrective actions | X | Planned in PA 2023.4 |
| Advanced chart presets | X | Planned in PA 2023.4 |
| Dynamic dropdown list selector to select model items | X | Planned in PA 2023.5 |
| Case level permissions for granular access control | X | Planned in PA 2023.5 |
| Loops and advanced programming logic in custom expressions | X | |
| Define custom aggregations using expressions | X | |
| Machine learning functionality (e.g., prediction, clustering) | X |