Data Archiving is part of the general Hyper Historian process. It makes it easier to access historical data using a high performance utility with a flexible architecture. Data Archiving in Hyper Historian can be configured via the Workbench. It currently supports both Azure SQL and Azure Data Lake.
Data synchronization is scheduled by Global Triggering system
Manual synchronization is supported (similar to re-calculation tasks)
Dataset based export
Support for miscellaneous data storages
Dataset filters and Data Storage connections can be aliased
Consists from Column and Filter Definitions (equivalent to SELECT and WHERE clause in SQL query)
Columns in datasets are defined by users
Can combine metadata, raw or aggregated values
Expression-based columns are supported
One dataset row can contain values from a single data point
Elements of value arrays can be mapped to separate columns
Performance calculations can be used to create row with values from multiple data points
Multiple aggregates of the same tag can be mapped to different columns
Data Point Filters can be aliased
File-based or table-based
Textual files formatted as CSV
Data can be organized based on time schedule (e.g. create new file every Monday, every day, etc.)
Connection string can be aliased
Storages supported
SQL Server
Azure SQL
Data Lake
Topmost entity – connects datasets and data storage
Scheduling
Alias definition
Multiple Datasets can be synchronized by a single task
Manual Synchronization is based on Tasks
Data Archiver extension is disabled by default.
To enable it, configuration structure has to be added to the Hyper Historian configuration.
In Workbench, select “Configure Database” and install “Hyper Historian – Data Archiver”.
See Also: