JDBC Data Source

Please enter the following parameters to connect to a JDBC data source:

Alias: name of the data source to be used in CData Virtuality Server
Host / Port: IP address or hostname and port of the server, where the data source is running
SSL: use encrypted connection (available for Redshift data source)
Schema / Database / SID / File etc.: schema / database name / SID / file path (depends on the data source type) of the data source to connect to
User name / Password: credentials to connect to the data source
Data source parameters: additional connection parameters
Auto-generated parameters: required additional connection parameters that are automatically generated by the wizard and appended to the configuration
Translator parameters: additional translator parameters
JDBC parameters: additional JDBC parameters

Below are some examples of the most common data source parameters, see the reference manual for the full list:

importer.useFullSchemaName=TRUE - schema names will be prefixed to table names to avoid duplicates
importer.importProcedures=TRUE - stored procedures will be imported
importer.useProcedureSpecificName=TRUE - when two stored procedures being imported have identical names, an index will be appended to their names in order to avoid conflicts

To test the connection parameters press the Test connection button.

Analytical Storage parameters

MySQL / MariaDB / AWS Aurora (MySQL Edition)

Schema: schema to hold analytical structures, can be arbitrarily chosen.
User name: arbitrary user with full rights on the schema entered above.
Data source parameters: importer.useFullSchemaName=FALSE, importer.tableTypes="TABLE,VIEW", importer.importIndexes=TRUE

MS SQL / MS SQL jTDS

Database: name of the database, can be arbitrarily chosen.
Schema: schema inside the database entered above to hold the analytical structures, can be arbitrarily chosen.
User name: arbitrary user with full rights on the schema entered above.
Data source parameters: importer.useFullSchemaName=FALSE, importer.tableTypes="TABLE,VIEW", importer.importIndexes=TRUE

Oracle

SID: system identifier, can be arbitrarily chosen.
Schema: schema inside the system entered above to hold the analytical structures, can be arbitrarily chosen.
User name: arbitrary user with full rights on the schema entered above.
Data source parameters: importer.schemaPattern=<schema>, importer.useFullSchemaName=FALSE, importer.tableTypes="TABLE,VIEW", importer.importIndexes=TRUE

PostgreSQL / AWS Aurora (PostgreSQL Edition)

Database: name of the database, can be arbitrarily chosen.
Schema: schema inside the database entered above to hold the analytical structures, can be arbitrarily chosen.
User name: arbitrary user with full rights on the schema entered above.
Data source parameters: importer.useFullSchemaName=FALSE, importer.tableTypes="TABLE,VIEW", importer.importIndexes=TRUE

RedShift

Database: name of the database, can be arbitrarily chosen.
Schema: schema inside the database entered above to hold the analytical structures, can be arbitrarily chosen.
User name: arbitrary user with full rights on the schema entered above.
Data source parameters: importer.useFullSchemaName=FALSE, importer.tableTypes="TABLE,VIEW"
Translator parameters: insertMultiThread=false, maxChunkSize=1600000, numberOfThreads=3

Vertica

Database: name of the database, can be arbitrarily chosen.
Schema: schema inside the database entered above to hold the analytical structures, can be arbitrarily chosen.
User name: arbitrary user with full rights on the schema entered above.
Data source parameters: importer.useFullSchemaName=FALSE, importer.tableTypes="TABLE,VIEW", importer.importIndexes=TRUE

EXASOL

This section shows all the possible table types that can be entered for a particular RDBMS server with the importer.tableTypes property.

DB2

MS SQL / MariaDB / AWS Aurora (MySQL Edition)

MySQL

PostgreSQL / AWS Aurora (PostgreSQL Edition)

Vertica

EXASOL