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17 may. 2018

Pentaho 8.1 ya esta aquí, conoce las novedades!!



Pentaho 8.1 ya esta disponible (aquí para descargar de Sourceforge) y que mejor que Pedro Alves para contarnos. Os dejamos las principales novedades y en que versión (EE o CE) están disponibles:

Cloud Google Storage (EE)

Google BigQuery – JDBC Support  (EE/CE)

Google BigQuery – Bulk Loader  (EE)


Google Drive  (EE/CE)

Analytics over BigQuery  (EE/CE, depending on the tool used)

Big Data / Adaptive Execution Layer (AEL) Improvements 

Bigger and Better (EE/CE)

Sub Transformation support (EE/CE)

Big Data formats: Added support for Orc (EE/CE)

Worker Nodes (EE)

New Streaming Datasources: MQTT, and JMS (Active MQ / IBM MQ) (EE/CE)


Safe Stop (EE/CE)

Streaming Dataservices (EE/CE)

CTools and Streaming Visualizations (EE/CE)

Time Series Visualizations (EE/CE)

Data Exploration Tool Updates (EE)


 Additional updates:

     Salesforce connector API update (API version 41)
     Splunk connection updated to version 7
     Mongo version updated to 3.6.3 driver (supporting 3.4 and 3.6)
     Cassandra version updated to support version 3.1 and Datastax 5.1
     PDI repository browser performance updates, including lazy loading
     Improvements on the Text and Hadoop file outputs, including limit and control file handling
     Improved logging by removing auto-refresh from the kettle logging servlet
     Admin can empty trash folder of other users on PUC
     Clear button in PDI step search in spoon
     Override JDBC driver class and URL for a connection
     Suppressed the Pentaho ‘session expired’ pop-up on SSO scenarios, redirecting to the proper login page
     Included the possibility to schedule generation of reports with a timestamp to avoid overwriting content

In summary (and wearing my marketing hat) with Pentaho 8.1 you can:

      Deploy in hybrid and multi-cloud environments with comprehensive support for Google Cloud Platform, Microsoft Azure and AWS for both data integration and analytics
      Connect, process and visualize streaming data, from MQTT, JMS, and IBM MQ message queues and gain insights from time series visualizations
      Get better platform performance and increase user productivity with improved logging, additional lineage information, and faster repository access

1 comentarios:

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