Data Stores
AspenTech Inmation OT DataFabric provides different types of data stores depending on the type of data that is being archived. The number of different data types produced by varying data sources means that one data store design is not sufficient to ensure effective and efficient storage and retrieval for each type. Therefore the system offers a number of dedicated Data Stores for different data types.
| No data stores are created automatically! To be able to archive data, a Data Store matching the type of data to be archived has to be created by an administrator. |
Time Series Data Store
The Time Series Data Store objects represent archives for time series data in MongoDB. Once they are created underneath a Node and are configured in Node’s Data Store Sets they are then available for selection in the Archive Selection menu for I/O items and other time series data producing objects in the namespace.
The time-series historization provides users with fast and secure access to data collected within any time interval and given update rate. AspenTech Inmation OT DataFabric makes use of aggregation concepts to be reliable at any time and to be able to answer requests within a minimum of time. All aggregates are calculated as specified within the OPC UA specification.
Writing to MongoDB uses an efficient write mechanism, that uses periodic bulk writes. The logic of the bulk writes follows the following principle: Historical data is accumulated in a buffer before it is written to MongoDB. The write cycle begins as soon as a minimum data volume threshold is met (Minimum Buffer Size), or a latency timer has elapsed ( Latency property.). This ensures efficient writing both for sustained loads, or peak loads in archiving operations.
Event Data Store
OPC Classic alarms and events as well as OPC UA produced alarms and conditions (OPC UA A+C) can be historized by using Event Data Store objects, according to the specification of the originating data source. Historized events can be quickly retrieved using the Event View in WebStudio or the AspenTech Inmation APIs (Lua, Web API).
| If Event Stream objects are configured to historize events, all events will be stored in any Event Data Store providing the event meets any configured filters. |
For more information on the storage schema for event documents, please visit the Lua geteventhistory function documentation.
Logging Data Store
The Logging Data Store is used to historize all log messages produced within the system. Log messages can be produced by any of the AspenTech Inmation components or objects within the system (including OPC datasources). Log messages can also be created using the Lua API with the syslib.log function.
By default, the Logging Data is stored in the system MongoDB. Alternatively SQLite can be selected in the Log Store Settings> Log Store Backend property of the Node object. When the Log Data Store is set to SQLite, the log messages will be stored in 'C:\AspenTech\inmation.root\work\core\db\log_<objectid>.db'.
Log messages can be retrieved from the Logging data store, either MongoDB or SQLite, using either the Log Display tab in WebStudio or the Lua API syslib.getlogs function.
Logs are purged from the Log Data Store based on the General Log Retention property.
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MongoDB and SQLite for Logging
It is important to note that using SQLite for the Logging Data Store may require more disk space than using MongoDB. Variations in query time are dependent on the configuration and hardware of the System and therefore, the overall performance of the query time for the Logging Data Store should not be largely affected by using either MongoDB or SQLite for the Log Store Backend. |