Pentaho

Name: Pentaho
Brand: Pentaho

Pentaho is a data integration and analytics platform that provides Pentaho Data Integration (PDI/Kettle) for building visual ETL/ELT pipelines, alongside reporting, dashboarding, and governance capabilities for hybrid on-prem and cloud deployments.

Est 2004|Valuation $600M|Raised $72M|8 Ref Customers

LinkedIn 29K|Web traffic 40K|FTEs 151

MarketsData Preparation Data Integration (ETL/ELT)

01Competitive Landscape

Narrative analysis

Where Pentaho tends to perform well: - Self-hosted control: organizations that require on-prem data retention or full infrastructure control. - Extensive ETL functionality: comprehensive built-in steps and a long-established ecosystem. - Embedded/Java-friendly environments: teams standardized on Java, on-prem schedulers, and central IT operations. Where competitors often have advantages: - Fivetran: transparent pricing mechanics and managed operations; faster time-to-ingestion for SaaS sources. - Matillion: cloud-native execution model and faster product development cadence; positions around usage-based credits and enterprise features like lineage/SSO in higher plans. - Airflow/Dagster (adjacent): code-first orchestration, testing, and observability aligned with software engineering workflows. - Airbyte (adjacent): open-source connector approach for modern ELT stacks. Customer sentiment comparisons (qualitative): - Community forums indicate some teams view Pentaho as legacy and are evaluating migrations to modern orchestrators (Airflow) or to Apache Hop for a more recently developed Kettle-like experience. - Review platforms show balanced perspectives, with many users reporting continued value, particularly for ETL and reporting flexibility.

	Pentaho (PDI/Platform)	Fivetran	Matillion
Starting Price	CE: free; EE: quote-based	Free plan available; then usage-based	Trial available; credit/consumption-based editions (quote/plan dependent)
Best For	Hybrid/self-hosted ETL; legacy-to-modern bridging; GUI ETL teams	Managed cloud ELT ingestion at scale; minimal ops	Cloud data pipeline builds with orchestration/transformation focus
Key Strength	Extensive visual ETL functionality, broad transformations, self-host control	Large managed connector catalog; transparent usage model; fast setup	Cloud-focused pipeline execution; consumption alignment; enterprise add-ons
Key Weakness	Pricing opacity; perceived legacy tooling; UI responsiveness; complex debugging	Cost can scale with data volume; less visibility into internals	Consumption pricing can be hard to forecast; cloud-centric assumptions

01Competitive Landscape

Narrative analysis

Where Pentaho tends to perform well:

Self-hosted control: organizations that require on-prem data retention or full infrastructure control.
Extensive ETL functionality: comprehensive built-in steps and a long-established ecosystem.
Embedded/Java-friendly environments: teams standardized on Java, on-prem schedulers, and central IT operations.

Where competitors often have advantages:

Fivetran: transparent pricing mechanics and managed operations; faster time-to-ingestion for SaaS sources.
Matillion: cloud-native execution model and faster product development cadence; positions around usage-based credits and enterprise features like lineage/SSO in higher plans.
Airflow/Dagster (adjacent): code-first orchestration, testing, and observability aligned with software engineering workflows.
Airbyte (adjacent): open-source connector approach for modern ELT stacks.

Customer sentiment comparisons (qualitative):

Community forums indicate some teams view Pentaho as legacy and are evaluating migrations to modern orchestrators (Airflow) or to Apache Hop for a more recently developed Kettle-like experience.
Review platforms show balanced perspectives, with many users reporting continued value, particularly for ETL and reporting flexibility.

	Pentaho (PDI/Platform)	Fivetran	Matillion
Starting Price	CE: free; EE: quote-based	Free plan available; then usage-based	Trial available; credit/consumption-based editions (quote/plan dependent)
Best For	Hybrid/self-hosted ETL; legacy-to-modern bridging; GUI ETL teams	Managed cloud ELT ingestion at scale; minimal ops	Cloud data pipeline builds with orchestration/transformation focus
Key Strength	Extensive visual ETL functionality, broad transformations, self-host control	Large managed connector catalog; transparent usage model; fast setup	Cloud-focused pipeline execution; consumption alignment; enterprise add-ons
Key Weakness	Pricing opacity; perceived legacy tooling; UI responsiveness; complex debugging	Cost can scale with data volume; less visibility into internals	Consumption pricing can be hard to forecast; cloud-centric assumptions