With the QlikView JDBC Connector, we provide QlikView users the opportunity to connect JDBC data sources (eg databases available without ODBC / OLEDB drivers such as Apache Derby / Java DB; big data environments) directly within QlikView. A direct database connection may prevented a complex exchange and integration of external files.
Furthermore, properties of the JDBC driver are configurable in the connection URL. Especially for installations of QlikView Version 9, a significant reduce of loading time can be achieved with the appropriate use and configuration of the JDBC driver instead of ODBC / OLEDB.
An additional functionality of the QlikView JDBC Connector is the improved support for writing back informations into connected databases. Within the QlikView script the execution of DML statements (eg 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 QlikView Version 11.2 (dependent on data sources SQL capability and JDBC driver implementation).
Possible QlikView data sources:
- Hadoop HDFS, Hive und Hive2
(Cloudera, Hortonworks, MapR, Amazon EMR)
- Cloudera Impala
- Apache HBase (via Phonix)
- Apache Cassandra CQL
- Amazon Redshift
- SAP S4/HANA ERP/BW
- SAP HANA DB
- SAP R/3 ERB/BW (via SAP JCo)
- hybris Virtual JDBC
- HP Vertica
- Kx Systems Kdb+ (unterstütz Q programming language)
- SAS Daten über Integrated Object Model (IOM)
- Microsoft Windows SQL Azure
- Google Cloud SQL
- Neo4j Graph Database (unterstütz Cypher graph query language)
- MongoDB (via UnityJDBC)
- OrientDB document graph NoSQL dbms
- Apache Derpy / Java DB, H2
- Verschlüsselte CSV Dateien (via CsvJdbc)
- COBOL Dateien (via HXTT Cobol)
- FoxPro / DBF (via HXTT DBF)
- Pentaho kettle Transformation Steps (via Carte Service)
Custom and optimized JDBC drivers
We develop custom and optimized JDBC drivers for several use cases (such as HDFS, FasterHive or Beeswax JDBC driver) based on its own JDBC Toolbox. Learn more about this on our GitHub Account.
As implementation partner of Qlik we have gathered many years of experience in the integration and development of Mashups, Extensions and Node.js services for QlikView.