Components reference

Pentaho aims to accommodate diverse computing environments. This list provides details about the environment components and versions we support. Where applicable, versions are listed as certified or supported:

• Certified

  The version has been tested and validated for compatibility with Pentaho.

• Supported

  Support is available for listed non-certified versions.

If you have questions about your particular computing environment, contact Pentaho Support.

Server operating system

The Pentaho Server is hardware-independent and runs on server-class computers.

Your server-class computer must comply with the specifications for minimum hardware and required operating systems:

Hardware	Certified Operating System - 64 bit	Supported Operating System - 64 bit
Processor Intel EM64T or AMD64 Dual-Core or later RAM 8 GB with 4 GB dedicated to Pentaho servers Disk Space 20 GB free after installation	Microsoft Windows 2025 Server Red Hat Enterprise 9* Ubuntu Server 22.04 LTS	Microsoft Windows 2022 Server Red Hat Enterprise 8*

*Pentaho Data Integration and Analytics is supported on any Linux distribution binary-compatible with RHEL 9 and Ubuntu Server 22, including in virtualized and cloud environments. If you have any questions, contact Pentaho Support.

Note: Mac servers are not supported as an operating system.

Container deployment

Supported technology for deploying Pentaho in containers.

Technology	Certified
Docker	27.5.1

Note: Kubernetes environments that use this Docker version are also supported.

You can also deploy pre-configured Docker images of specific Pentaho products in your AWS environments. See Docker container deployment of Pentaho Server and Docker container deployment of Carte, Pan, and Kitchen for details.

Workstation operating system

These Pentaho design tools are hardware-independent and run on client-class computers that comply with these specifications for minimum hardware and required operation systems.

• Pentaho Aggregation Designer

• Pentaho Data Integration

• Pentaho Metadata Editor

• Pentaho Report Designer

• Pentaho Schema Workbench

Hardware - 64 bit	Certified Operating System - 64 bit	Supported Operating System - 64 bit
Processors Apple Macintosh Dual-Core Apple Mac M1, M2, and M3 chipset Intel EM64T or AMD64 Dual-Core or later RAM 2 GB RAM for most of the design tools, PDI requires 2 GB dedicated Disk Space 2 GB free after installation Minimum Screen Size 1280 x 960 pixels	Ubuntu Desktop 22.04 Microsoft Windows 11 macOS 15 (Sequioa)	macOS 14 (Sonoma)

Note: Ubuntu Linux requires `libwebkitgtk-1.0`. See Install Pentaho Data Integration and Analytics for more information.

Embedded software

When embedding Pentaho software into other applications, the computing environment should comply with these specifications for minimum hardware and required operation systems.

• Embedded Pentaho Reporting

• Embedded Pentaho Analysis

• Embedded Pentaho Data Integration

Note: Pentaho Data Integration and Analytics is officially certified to run on the Red Hat Enterprise and Ubuntu Linux distributions. It is compatible with any binary-compatible Linux distribution that meets the necessary software and hardware requirements, including in virtualized and cloud environments. If you have any questions, contact Pentaho Support.The following specifications comply with minimum hardware and required operating systems for embedding Pentaho reporting, analysis, and data integration:

Hardware—64 bit	Certified Operating System—64 bit
Processors Intel EM64T or AMD64 Dual-Core RAM 8 GB with 4 GB dedicated to Pentaho servers Disk Space 20 GB free after installation	Microsoft Windows 2022 Server Red Hat Enterprise 9 Ubuntu Server 22.04 LTS

Application servers

The server to which you deploy Pentaho software must run the following application server:

• Tomcat 10.1.48 (Certified)

Solution database repositories

Pentaho software stores processing artifacts in these database repositories:

Repository	Certified	Supported
PostgreSQL	16	15
MySQL	8.4
Oracle	23c & 23ai
MS SQL Server	2022	2019 (including patched versions)
Maria DB	11.4

* The default installed solution database.

Apache Hadoop vendors

Pentaho software has certified or supported data sources from these Hadoop Vendors.

Vendor	Driver Version
Amazon EMR	7.7.0
Cloudera Data Platform (CDP) Private Cloud	7.1.x, 7.3.1

Data Sources: Pentaho Tools

This table summarizes which data sources are compatible with the main Pentaho tools.

Pentaho Software	Data Source
Pentaho Reporting	JDBC 3/41 ODBC OLAP4J XML Pentaho Analysis Pentaho Data Integration Pentaho Metadata Scriptable Snowflake
Pentaho Server, Action Sequences	Relational (JDBC) Hibernate Javascript Metadata (MQL) Mondrian (MDX) XML (XQuery) Security User/Role List Provider Snowflake Data Integration Steps (PDI) Other Action Sequences Web Services XMLA
Pentaho Data Integration	JDBC 3/41 OLAP4J Salesforce Snowflake XML CSV Microsoft Excel

¹ Use a JDBC 3.x or 4.x compliant driver that is compatible with SQL-92 standards when communicating with relational data sources. For a list of drivers to use with relational JDBC databases, see the JDBC drivers reference.

Big Data Sources: General

Pentaho software supports the following Big Data sources. Check this list if you are evaluating Pentaho or checking for general compatibility with a specific vendor.

Data Source	Certified	Supported
Amazon EMR (via Hive)	7.7.0
Cassandra (Datastax)	6.8
Cloudera Data Platform (CDP) on premises (private cloud)	7.1.9
Google BigQuery (Simba)	1.6.2	1.2.25
MongoDB	7.0
Vertica*	24

^* Deprecated beginning in version 11.0.

Big Data Sources: Details

This table shows the Big Data sources that are compatible with specific Pentaho tools.

Data Source	Versions	Analyzer	PIR/PDD	Pentaho Reporting	DSW	PDIServer/Client	PRD	PSW	PME
Amazon EMR	7.7.01 (Certified)	No	No	No	No	Yes	Yes	No	No
Cassandra (Datastax)	6.8 (Certified)	No	No	No	No	Yes	No	No	No
Cloudera Data Platform (CDP) Private Cloud	7.1.9 (for job execution)	No	No	No	No	Yes	Yes	No	Yes
Cloudera Data Platform (CDP) Private Cloud	via Impala (as data source)	Yes	Yes	Yes	Yes	Yes	Yes	No	Yes
Cloudera Data Platform (CDP) Private Cloud	via Hive32 (as data source)	No	Yes	Yes	Yes	Yes	Yes	No	Yes
Google BigQuery	1.5.4.10083	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
MongoDB	7	No	No	Yes	No	Yes	Yes	No	No
Vertica4	11	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes

¹ EMR clusters (version 7.x and later) built with JDK 17 exclude the commons-lang-2.6.jar library from their standard Hadoop library directories ($HADOOP_HOME/lib). To use the EMR driver for EMR 7.x, obtain the commons-lang-2.6.jar file from a trusted source, such as the official Maven repository (Maven Repository: commons-lang » commons-lang » 2.6). Then manually copy the downloaded JAR file to the $HADOOP_HOME/lib or $HADOOP_MAPRED_HOME/lib directory on each node within the EMR cluster to ensure that all worker nodes have access to the library.

² Hive3 as a data source for CDP also supports Hive LLAP, and Hive3 on Tez.

³ The Simba driver required for Google BigQuery is the JDBC 4.2-compatible version, which you can download from https://storage.googleapis.com/simba-bq-release/jdbc/SimbaJDBCDriverforGoogleBigQuery42_1.2.2.1004.zip.

⁴ Deprecated beginning in version 11.0.

Note: A generic Apache Hadoop driver is included in the Pentaho distribution for version 10.2: Other supported drivers can be downloaded from the Support Portal.

SQL Dialect-Specific

Pentaho software generates dialect-specific SQL when communicating with these data sources. Certified indicates the SQL dialect has been tested for compatibility with Pentaho.

Pentaho Software	Data Source
Pentaho Analyzer	Certified Amazon Redshift Azure SQL Impala MySQL Microsoft SQL Server Oracle PostgreSQL Snowflake Supported Access Firebird Hsqldb IBM DB2 IBM MQ 9.2 Informix Ingres1 Interbase1 Neoview1 SqlStream Sybase1 Vectorwise1 Vertica1 Other SQL-89 compliant2
Pentaho Metadata	Certified Azure SQL Hive 2 Impala MySQL PostgreSQL Supported Amazon Redshift ASSQL Firebird H2 Hypersonic IBM DB2 IBM MQ 9.2 Ingres1 Interbase1 MS Access MS SQL Server (JTDS Driver) MS SQL Server (Microsoft Driver) Snowflake Sybase1 Vertica1 Other SQL-92 compliant2
Pentaho Data Integration	Certified Amazon Redshift Azure SQL Hive1 Hive 2 Impala MS SQL Server (JTDS Driver) MS SQL Server (Microsoft Driver) MySQL Oracle PostgreSQL Snowflake Vertica1 Supported AS/400 InfiniDB1 Exasol 4 Firebird SQL H2 Hypersonic IBM DB2 IBM MQ 9.2 Informix Ingres1 Ingres VectorWise1 MaxDB (SAP DB) Neoview1 Oracle RDB SQLite UniVerse database Other SQL-92 compliant2

¹ Deprecated beginning in version 11.0.

² If your data source is not in this list and is compatible with SQL-92, Pentaho software uses a generic SQL dialect.

Security

Pentaho software integrates with these third-party security authentication systems:

• CAS 7 (Certified)

• Integrated Windows Authentication with Internet Information Services 10 (Certified)

• Spring 6.2.12 (Certified)

Java virtual machine

Pentaho software requirements for Java Runtime Environment (JRE).

Pentaho Software	Certified	Supported
All Pentaho software	Oracle Java 21 Oracle OpenJDK 21	Oracle Java 17 Oracle OpenJDK 17

Note: The PDI client requires at least Java 11.x to run on Windows 11.

Web browsers

Pentaho supports major versions of web browsers that are publicly available six weeks before the finalization of a Pentaho release.

The following browsers are certified:

• Apple Safari 26.1 (On macOS only)

• Google Chrome 142

• Microsoft Edge 142

• Mozilla Firefox 144

Support Statement for Analyzer on Impala

These are the minimum requirements for Analyzer to work with Impala:

• Pentaho 7.1 or later

• Impala 1.3.x or later

• Recommend using Parquet compressed file format for tables in Impala

• Make sure that the JDBC driver is dropped into the Pentaho Server and Schema Workbench directories. See the Install Pentaho Data Integration and Analytics document for details.

• Turn off connection pooling in Pentaho Server.

• In Mondrian schemas, divide dimension tables with high cardinality into several levels

Note: As with any data source, the performance of Pentaho Analyzer on Impala will be dependent upon the data shape, Impala’s configuration, and the types of queries. See the best practice, "Pentaho Analyzer with Impala as a Data Source" located at: https://support.pentaho.com/hc/en-us/articles/208652846 or download the PDF.

There are some compiled Mondrian automated test suite results for Analyzer on Impala with OEM Simba, as well as the community Apache Hive driver:

• Analyzer on Impala with OEM Simba

• Analyzer on Impala with community Apache Hive driver

Google BigQuery

You can use Google BigQuery as a data source with the Pentaho User Console or with the PDI client.

Before you begin, you must have a Google account and must create service account credentials in the form of a key file in JSON format to connect to Google BigQuery. To create service account credentials, see the Google Cloud Storage Authentication documentation.

Additionally, you must set permissions for your BigQuery and Google Cloud accounts. To configure your service account authentication, see the Google Service Account documentation.

Perform the following steps to create a JDBC connection to a Google BigQuery data source from the User Console or PDI client.

1. Stop the Pentaho Server.

2. Download the ZIP file containing the Simba version 1.5.4.1008 JDBC 4.2 driver for Google BigQuery from https://storage.googleapis.com/simba-bq-release/jdbc/SimbaJDBCDriverforGoogleBigQuery42_1.2.2.1004.zip.

3. Navigate to the server/pentaho-server/tomcat/webapps/pentaho/WEB-INF/lib directory for the User Console or the design-tools/data-integration/lib directory for the PDI client and delete any files associated with previous versions of Google BigQuery.

   Visually verify each file to ensure the older version is deleted.

4. Extract the following files to the server/pentaho-server/tomcat/webapps/pentaho/WEB-INF/lib folder for the User Console or the design-tools/data-integration/lib directory for the PDI client.

   • animal-sniffer-annotations-1.14.jar

   • api-common-1.7.0.jar

   • avro-1.9.0.jar

   • checker-compat-qual-2.5.2.jar

   • error_prone_annotations-2.1.3.jar

   • gax-1.42.0.jar

   • gax-grpc-1.42.0.jar

   • google-api-client-1.28.0.jar

   • google-api-services-bigquery-v2-rev426-1.25.0.jar

   • google-auth-library-credentials-0.15.0.jar

   • google-auth-library-oauth2-http-0.13.0.jar

   • GoogleBigQueryJDBC42.jar

   • google-cloud-bigquerystorage-0.85.0-alpha.jar

   • google-cloud-core-1.67.0.jar

   • google-cloud-core-grpc-1.67.0.jar

   • google-http-client-1.29.0.jar

   • google-http-client-apache-2.0.0.jar

   • google-http-client-jackson2-1.28.0.jar

   • google-oauth-client-1.28.0.jar

   • grpc-alts-1.18.0.jar

   • grpc-auth-1.18.0.jar

   • grpc-context-1.18.0.jar

   • grpc-core-1.18.0.jar

   • grpc-google-cloud-bigquerystorage-v1beta1-0.50.0.jar

   • grpc-grpclb-1.18.0.jar

   • grpc-netty-shaded-1.18.0.jar

   • grpc-protobuf-1.18.0.jar

   • grpc-protobuf-lite-1.18.0.jar

   • grpc-stub-1.18.0.jar

   • gson-2.7.jar

   • j2objc-annotations-1.1.jar

   • javax.annotation-api-1.3.2.jar

   • jsr305-3.0.2.jar

   • opencensus-api-0.18.0.jar

   • opencensus-contrib-grpc-metrics-0.18.0.jar

   • opencensus-contrib-http-util-0.18.0.jar

   • protobuf-java-3.7.0.jar

   • protobuf-java-util-3.7.0.jar

   • proto-google-cloud-bigquerystorage-v1beta1-0.50.0.jar

   • proto-google-common-protos-1.15.0.jar

   • proto-google-iam-v1-0.12.0.jar

   • threetenbp-1.3.3.jarNote: The Google BigQuery connection name does not display in the User Console Database Connection dialog box until you copy these files.

5. Restart the Pentaho Server.

6. Log on to the User Console or the PDI client, then open the Database Connection dialog box.

   See the Install Pentaho Data Integration and Analytics document for more information on the Database Connection dialog box.

7. In the Database Connection dialog box, select General, then select Google BigQuery as the Database Type.

8. In the Settings area, enter the information for your Google BigQuery account.

   • The Host Name is the URL to Google's BigQuery web services API. For example, https://www.googleapis.com/bigquery/v2

   • The Project ID in the PDI client and the Database name in the User Console are identical.

   • The Port Number is 443.

9. Click Options, then add the following parameters and values.

   Parameter	Value
   OAuthType	0 (Zero)
   OAuthServiceAcctEmail	Specify your service account email address.
   OAuthPvtKeyPath	Specify the path to your private key credential file.
   Timeout	Specify the amount of time, in seconds, before the server closes the connection. The recommended value is 120 seconds.

10. Click Test to verify that you can connect to your data.