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Pentaho EE OnPrem
Pentaho EE Data Integration & Analytics installers you can install on-premises.
Pentaho EE Cloud
Pentaho EE Data Integration & Analytics Docker images, configured to run on AWS, Google Cloud or Azure
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Which Pentaho Experience is Right for You?

Compare key differences between various versions - Pentaho Community vs Pentaho Enterprise.

Features Pentaho
Codeless pipeline development
Enterprise-scale load balancing & scheduling
Streaming data support
Easy Kettle to Spark execution
Expanded library of connectors
Data science toolkit
Professional services packages
IP protection
Connector support for cloud, big data,
streaming, data catalog
Enterprise components for
business analytics
Report capabilities
Pentaho user console
Containerization and hyperscaler suppport
Metadata injection at scale
Full meta editor
Data source wizard
Schema workbench
Advanced encryption standard (AES)
Technical support options 24/7 availability, assigned
architect, mentoring
Forums, community,
how-to videos
Release schedule Major releases, security and
monthly patches
Only major releases
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Accelerate Your Data Transformation With Pentaho

Pentaho Enterprise Hands-On Experience

Get a hands-on experience of enterprise-class data integration and analytics software for scaling big data, multicloud migration and integration with applications and services.

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Pentaho Enterprise Edition Free 30-Day Trial

Download Pentaho and try the full enterprise-class data integration & analytics software scaling for big data, multicloud migrations and integration into applications and services. Provides the complete set of features.

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Pentaho Community Edition

Pentaho Community Edition is an open-source version with core engines in the platform that lets you experiment with reduced features and capabilities. Extract, transform and load (ETL) limited data.

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Pentaho(EE) Data Integration & Analytics: Plugins Marketplace

Google Analytics v4

Google Analytics v4: You can use the Google Analytics v4 step to access your Google Analytics data to generate reports or to populate your data warehouse. This step queries Google Analytics properties using the Google Analytics API v4 and places the resulting dimension and metric values on the step output stream. Note: Google Analytics v4 API is currently in Beta and the libraries that are shipped along with this new plugin are in Beta. General availability of the Google API is not available yet. For more information please refer to
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Salesforce Bulk Operation Plugin

This plugin allows you to use the Salesforce Bulk Operation step if you have a large number of Salesforce objects to INSERT, UPDATE, UPSERT, or DELETE. The step provides seamless bulk job orchestration and significantly faster Salesforce object manipulation than the traditional SOAP steps offer.
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Elasticsearch REST Bulk Insert

This plugin allows you to use the Elasticsearch REST Bulk Insert step if you have records that you want to submit to an Elasticsearch server 8x installed for indexing. Use this step to send one or more batches of records to an Elasticsearch server for indexing. Because you can specify the size of a batch, you can use this step to send one, a few, or many records to Elasticsearch for indexing.
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Databricks Bulk Loader

This plugin allows you to use the Databricks Bulk Loader step if you have load large amount of data from files in cloud account into databricks tables and enables use cases where bulk operations are required. The step uses the COPY INTO command to load the data, and most of the options are driven by that command.
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Elasticsearch Plugin

Use the Elasticsearch REST Bulk Insert step if you have records that you want to submit to an Elasticsearch server for indexing. This plugin now supports Elasticsearch 8 and paves the way to use PDI in the future with the increasingly popular OpenSearch/AWS version of Elasticsearch.
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Hierarchical Data Type (HDT)

Hierarchical Data Type (HDT) is a new datatype in PDI for handling structured/complex/nested datatype based on JSON format. There are five new plugins/steps namely Hierarchical JSON Input, Extract to Rows, Modify values from a single row, Modify values from grouped rows and Hierarchical JSON Output. Hierarchical JSON Input step takes JSON /JSONL from previous step or from the file location and converts into a Hierarchical object. Hierarchical JSON Output step is used to get data in HDT from previous steps and convert it into JSON formatted string. And the other three steps are used for manipulating the Hierarchical Data Type.
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Kafka EE (Enterprise Edition)

Kafka EE is an upgraded version of Kafka CE Plugin with additional enterprise features enabled. It now supports SSL and Kerberos to connect broker and new Job entry called Kafka Offset is added to reset offset of Kafka topic partitions. Also included is the ability to stop reading messages by Kafka consumer, once the offset is reached by taking timestamp as input (ex: future/past timestamp) using Kafka Offset job entry. And finally, Kafka consumer step user can read messages from start offset to end offset from different partitions of a topic.
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