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Comparing FME with Pentaho Data Integration and Weld

You’re comparing FME vs Pentaho Data Integration vs Weld. Explore how they differ on connectors, pricing, and features. Ed Logo

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Weld vs FME vs Pentaho Data Integration

WeldFMEPentaho Data Integration
Connectors200+450+150+
Price$99 / 5M Active RowsPer-seat for FME Desktop ($2,000+/year) and per-core for FME Server (custom)Community Edition: Free; Enterprise Edition: Custom pricing
Free tier
LocationEUSurrey, BC, Canada (Safe Software HQ)Santa Clara, CA, USA (Hitachi Vantara HQ)
Extract data (ETL)
Sync to HubSpot, Salesforce, Klaviyo, Excel (reverse ETL)
Transformations
AI Assistant
On-Premise
Orchestration
Lineage
Version control
Load to/from ExcelYes (via Excel reader/writer)Yes (Excel/CSV input/output)
Load to/from Google SheetsYes (via Google Sheets plugin)
Two-Way Sync
dbt Core Integration
dbt Cloud Integration
OpenAPI / Developer API
G2 rating4.84.74.1

Overview

FME in Short

FME (by Safe Software) is a data integration and transformation platform primarily focused on spatial and GIS data, but it also supports a wide range of non-spatial ETL. It provides a graphical workspace where users can build data pipelines, handling over 450 formats and applications, with strong data quality and validation capabilities.

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Pros

  • Supports 450+ data formats, making it ideal for GIS and non-GIS integration.

  • Graphical Workspaces with extensive transformer library for spatial (coordinate reprojection, topology) and non-spatial transformations (joins, data cleansing).

  • FME Server enables automated scheduling, breakout clustered processing, and REST API for triggering workflows.

  • Strong data validation and quality features—users can apply conditional checks and notifications when data doesn’t meet criteria.

Cons

  • High licensing costs for desktop (FME Desktop) and server components; often priced per core for server deployments.

  • Primarily geared toward GIS/spatial use cases; non-spatial ETL use is possible but the interface and transformers are optimized for spatial workflows.

  • Large learning curve for complex workspaces—dragging many transformers can become unwieldy visually.

Reviews & Quotes

FME Product Overview:

What I like about FME

FME’s ability to handle complex spatial transformations and 450+ formats is unmatched. The drag-and-drop workspace builder drastically speeds up geospatial ETL.

What I dislike about FME

Licensing can be expensive for smaller organizations. Focus on spatial means some general ETL features are less polished than GIS-specific functions.

Overview

Pentaho Data Integration in Short

Pentaho Data Integration (PDI), also known as Kettle, is an open-source ETL tool from Hitachi Vantara. It provides a graphical Spoon interface for building ETL transformations and jobs, supporting over 150 data sources (relational, NoSQL, cloud, files). PDI includes built-in steps for data cleansing, join, lookup, and can execute transformations in a clustered environment. It also integrates with Pentaho’s BI platform for analytics.

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Pros

  • Open-source (Community Edition) with no licensing costs; Enterprise Edition provides additional features and support.

  • 150+ connectors (databases, cloud storage, big data, files, NoSQL) and flexible step-based transformations.

  • Graphical Spoon interface for visual ETL job design; transformations can be previewed and tested in real-time.

  • Support for clustered execution (Carte server) for parallel processing and higher throughput.

Cons

  • Community Edition lacks advanced features (lineage, data quality, enterprise monitoring), requiring Enterprise Edition for production readiness.

  • Performance can suffer with very large data volumes if not properly tuned (Java memory, clustering).

  • User interface and user experience are dated compared to newer cloud-native ETL tools.

Reviews & Quotes

Pentaho Data Integration Overview:

What I like about Pentaho Data Integration

PDI’s free community edition and Spoon GUI allow rapid ETL prototyping; its step library is extensive, and clustering support is solid for scale.

What I dislike about Pentaho Data Integration

Limited data quality features and slower development speed compared to modern cloud ETL. Community support can be slow for fixes.

Overview

Weld in Short

Weld is a powerful ETL platform that seamlessly integrates ELT, data transformations, reverse ETL, and AI-assisted features into one user-friendly solution. With its intuitive interface, Weld makes it easy for anyone, regardless of technical expertise, to build and manage data workflows. Known for its premium quality connectors, all built in-house, Weld ensures the highest quality and reliability for its users. It is designed to handle large datasets with near real-time data synchronization, making it ideal for modern data teams that require robust and efficient data integration solutions. Weld also leverages AI to automate repetitive tasks, optimize workflows, and enhance data transformation capabilities, ensuring maximum efficiency and productivity. Users can combine data from a wide variety of sources, including marketing platforms, CRMs, e-commerce platforms like Shopify, APIs, databases, Excel, Google Sheets, and more, providing a single source of truth for all their data.

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Pros

  • Lineage, orchestration, and workflow features

  • Ability to handle large datasets and near real-time data sync

  • ETL + reverse ETL in one

  • User-friendly and easy to set up

  • Flat monthly pricing model

  • 200+ connectors (Shopify, HubSpot, etc.)

  • AI assistant

Cons

  • Requires some technical knowledge around data warehousing and SQL

  • Limited features for advanced data teams

  • Focused on cloud data warehouses

Reviews & Quotes

A reviewer on G2 said:

What I like about Weld

First and foremost, Weld is incredibly user-friendly. The graphical interface is intuitive, which makes it easy to build data workflows quickly and efficiently. Even with little experience in SQL and pipeline management, we found that Weld was straightforward and easy to use. What really impressed me, however, was Weld's flexibility. It was able to handle data from a wide variety of sources, including SQL databases, Google Sheets, and even APIs. The solution also allowed us to customize my data transformations in a way that best suited my needs. Whether I needed to clean data, join tables, or aggregate data, Weld had the necessary tools to accomplish the task. Weld's performance was also exceptional. I was able to run large-scale ETL jobs quickly and efficiently, with minimal downtime via a Snowflake instance and visualization via own-hosted Metabase. The solution's scalability meant that I could process more data without any issues. Another standout feature of Weld was its support. I never felt lost or unsure about how to use a particular feature, as the support team was always quick to respond to any questions or concerns that I had. Overall, I highly recommend Weld as an ETL solution. Its user-friendliness, flexibility, performance, and support make it an excellent choice for anyone looking to streamline their data integration processes. I will definitely be using Weld for all my ETL needs going forward.

What I dislike about Weld

Weld is still limited to a certain number of integrations - although the team is super interested to hear if you need custom integrations.

Feature-by-Feature Comparison

Feature
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FME

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Pentaho Data Integration

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Weld

Ease of Use & Interface

Side-by-side

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FME

FME’s Workbench is a desktop application where users connect Reader and Writer transformers to map and transform data. While powerful for spatial, the GUI can feel cluttered for workflows with hundreds of transformers.

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Pentaho Data Integration

Pentaho’s Spoon GUI uses a canvas paradigm: drag "steps" onto a transformation, connect them, and configure. While powerful, it can feel clunky, especially for very complex flows with many steps.

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Weld

Weld is highly praised for its user-friendly interface and intuitive design, which allows even users with minimal SQL experience to manage data workflows efficiently. This makes it an excellent choice for smaller data teams or businesses without extensive technical resources.

Pricing & Affordability

Side-by-side

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FME

FME Desktop licenses start around $2,000/year. FME Server pricing is per-core (often $20k+/core for an annual license). Expensive for small teams, but justified where spatial data integration is critical.

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Pentaho Data Integration

The free Community Edition is attractive for experimentation. Enterprise Edition pricing is usage-based and includes support, lineag, and more; typically suited for mid-sized to large organizations.

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Weld

Weld offers a straightforward and competitive pricing model, starting at $79 for 5 million active rows, making it more affordable and predictable, especially for small to medium-sized enterprises.

Feature Set

Side-by-side

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FME

Supports reading/writing 450+ formats (GIS, CAD, JSON, XML, databases), transformer library (spatial & non-spatial), workflow orchestration via FME Server, automation (event-based, scheduled), and REST API endpoints for triggering.

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Pentaho Data Integration

PDI features: GUI-based transformation designer, job orchestration, data cleansing, lookups, joins, scripting (JavaScript, PDI’s built-in “User Defined Java Expression”), logging, clustering, and integration with Pentaho BI for reporting. Lineage and monitoring in Enterprise.

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Weld

Weld integrates ELT, data transformations, and reverse ETL all within one platform. It also provides advanced features such as data lineage, orchestration, workflow management, and an AI assistant, which helps in automating repetitive tasks and optimizing workflows.

Flexibility & Customization

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FME

Users can embed Python, R, or Shell scripts within transformers for custom logic. FME Server can be deployed in any environment (on-prem, AWS, Azure) and scaled horizontally. However, no built-in data catalog or lineage; separate tools needed.

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Pentaho Data Integration

Users can embed Java, JavaScript, or invoke external scripts. PDI’s open architecture allows custom plugins for new steps/connectors. The code is open-source, so full extensibility is available, though it requires Java development.

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Weld

Weld offers advanced SQL modeling and transformations directly within its platform with the help of AI, providing users with unparalleled control and flexibility over their data. Leveraging its powerful AI capabilities, Weld automates repetitive tasks and optimizes data workflows, allowing teams to focus on getting value and insights. Additionally, Weld's custom connector framework enables users to build connectors to any API, making it easy to integrate new data sources and tailor data pipelines to meet specific business needs. This flexibility is particularly beneficial for teams looking to customize their data integration processes extensively and maximize the utility of their data without needing external tools.

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