PostgreSql or protocol-compatible database (like Amazon Redshift) can be used as a data source with SQL-compatible database connector.
There are no any limitations on the dataset size; your PostgreSql should be able to execute aggregate queries fast enough (in seconds; 2 minutes max). In case of large datasets you may pre-aggregate the data with materialized view, apply some filters on indexed columns, or use PipelineDB extension for real-time aggrations.
Connection String should be a valid connection string for NpgSql driver; for example:
Specifies the host name of the machine on which the PostgreSql is running.
Do not use "localhost" or LAN server name; use only public IP address or server's domain name.
|Database||The PostgreSQL database to connect to.|
|User ID||The username to connect with.|
|Password||The password to connect with.|
|Trust Server Certificate||Specify
|Server Compatibility Mode||Specify
Trust Server Certificate=Trueto the connection string to disable SSL certificate validation (needed if your server uses self-signed certificate).
some_column < 5this means that
some_columnis TEXT type. To fix this go to the cube configuration form, find the dimension with Name "some_column" and add a Parameter to define SQL expression with a cast:
some_column="2019-05-15"this means that column's data type is Date (or DateTime) and it cannot be compared with TEXT value. To fix this go to the cube configuration form, find the dimension with Name "some_column" and add a Parameter to define SQL expression with a cast:
ConvertInfinityDateTime=Trueto the connection string; if this doesn't help you need to exclude unpresentable timestamps from the query results (either by WHERE filtering or by timestamp normalization with an SQL expression).