Understand how caching and datasource queries work in Push.ai.
Push.ai uses a caching strategy to optimize application performance, while reducing the load on your data sources.
Push.ai queries datasources through two methods:
Caching is used when querying both calculations and timeseries data. Push.ai implements a caching strategy for each unique metric-dimension combination. For each combination, we maintain a daily cache, meaning that we will query that specific combination from the data source at most once per day.
Push.ai queries datasources using two methods:
If multiple users are subscribed to the same Business Object, the datasource query will be triggered once for each object, rather than once for each user.
Datasource compute is not used in any of Push.ai’s advanced analytics or AI applications. This includes time-series modeling, such as outlier detection and forecasting. In addition, Push.ai’s AI systems combine the existing calculations with large language models, and do not use additional datasource compute.
Understand how caching and datasource queries work in Push.ai.
Push.ai uses a caching strategy to optimize application performance, while reducing the load on your data sources.
Push.ai queries datasources through two methods:
Caching is used when querying both calculations and timeseries data. Push.ai implements a caching strategy for each unique metric-dimension combination. For each combination, we maintain a daily cache, meaning that we will query that specific combination from the data source at most once per day.
Push.ai queries datasources using two methods:
If multiple users are subscribed to the same Business Object, the datasource query will be triggered once for each object, rather than once for each user.
Datasource compute is not used in any of Push.ai’s advanced analytics or AI applications. This includes time-series modeling, such as outlier detection and forecasting. In addition, Push.ai’s AI systems combine the existing calculations with large language models, and do not use additional datasource compute.