With the QlikView JDBC Connector, TIQ Solutions provides QlikView users the opportunity to connect JDBC data sources (e.g. databases such as Derby / Java DB or Java-based big data environments that are available without ODBC / OLEDB drivers) directly within QlikView. Without the QlikView JDBC Connector, a direct database connection may prevent a complex exchange and integration of external files. It is possible now, for example, to integrate data from hadoop / hive into QlikView.
Furthermore, properties of the JDBC driver are configurable in the connection URL. Especially for installations of QlikView Version 9, a significant reduction of loading time can be achieved with the appropriate use and configuration of the JDBC driver instead of ODBC / OLEDB.
An additional feature of the QlikView JDBC Connector is improved support for writing back information into connected databases. Within the QlikView script the execution of DML statements (e.g. insert / update / delete) returns a result set with the number of changed rows. Hereby it is now possible, for example, to integrate QlikView into workflow processes with a write-back of status information.
The QlikView JDBC Connector supports QlikView Direct Discovery coming with version 11.2.
Possible JDBC data sources:
- Hadoop HDFS, Hive, Hive2 and Impala (Cloudera, MapR, Amazon EMR)
- SAP HANA
- SAP ERP/BW (via SAP JCo)
- Kx Systems Kdb+ (supports Q language)
- Neo4j Graph Database (supports Cypher graph query language)
- Microsoft Windows SQL Azure
- Google Cloud SQL (mysql)
- Pentaho Kettle Transformation Steps (via Carte service)
- Apache Derby / Java DB
- encrypted CSV files
- COBOL files
- FoxPro / DBF files
A list of JDBC drivers and vendors can be found at: http://www.sqlsummit.com/JDBCVend.htm.
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TIQ Solutions GmbH offers methodological and technical consulting services for quality-assured data management. We support our customers from the initial needs analysis to full implementation in the areas of data integration, data migration, business intelligence and data warehousing, as well as in the management of master data and metadata.