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Datasheet:Pentaho Data Integration

With Pentaho Data Integration - Managing the enormous volumes, variety, and velocity of data is simplified

By allowing data preparation from any source and automating your data pipeline, Pentaho Data Integration allows you to curate data better for your business user. This software delivers business analytics to end users faster with visual tools that reduce time and complexity - without writing SQL or coding in Java or Python. Organizations immediately gain real value from their various data sources in the cloud or on premises, including files, relational databases, big data sets and more.

Turn Data Into Actionable Insights

More than just ETL (Extract, Transform, Load), Pentaho Data Integration is a codeless data orchestration tool that blends diverse data sets into a single source of truth as a basis for analysis and reporting. Effortlessly managed in a drag-and-drop graphical interface, so you can easily track where it's coming from, where it's going and how it's transforming.

Data Processing Performance and Productivity

PDI speeds performance time, reduces the complexity of integrating big data sources, and provides:

• Code-free data transformation
• Template-based approach to rapidly onboard data sources into Hadoop

Scalability, Simplicity, and Self-Service

With broad connectivity to any data type and high-performance Spark and MapReduce execution, PDI simplifies and speeds the process of integrating existing databases with new sources of data.

• Intuitive, drag-and-drop designer
• Rich library of prebuilt components
• Powerful orchestration capabilities

Integration and Extensibility

• API Integration: Comprehensive REST and SOAP APIs
• Plugin Architecture: Extend capabilities with a rich plugin ecosystem
• Third-Party Tool Integration: BI tools, databases, etc

Broad Connectivity and Data Delivery

PDI offers broad connectivity to a variety of diverse data, including structured, unstructured and semi-structured data.

• Relational database management system (RDBMS): Oracle, IBM DB2, MySQL, Microsoft SQL Server, Postgres, IBM MQ
• Spark and Hadoop: Cloudera, Hortonworks, Amazon EMR, MapR (HPE Ezmeral Data Fabric), Microsoft Azure HDInsights, and Elastic Search
• NoSQL databases and object stores: MongoDB, Cassandra, HBase, Hitachi Content Platform, AWS S3, Google Cloud Storage, Microsoft Azure ADLS Gen 2
• Analytic databases: Redshift, Snowflake, Vertica, Greenplum, Teradata, SAP HANA, Amazon Redshift, Google Big Query
• Business applications: SAP, Salesforce, Google Analytics
• Files: XML, JSON, Microsoft Excel, CSV, txt, Avro, Parquet, ORC, EBCDIC (mainframe), unstructured files with metadata, including audio, video and visual files