Comparing IBM DataStage with Pentaho Data Integration and Weld

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

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Weld vs IBM DataStage vs Pentaho Data Integration

	Weld	IBM DataStage	Pentaho Data Integration
Connectors	200+	200+	150+
Price	$99 / 5M Active Rows	Enterprise licensing (custom, usually six-figure annual)	Community Edition: Free; Enterprise Edition: Custom pricing
Free tier
Location	EU	Armonk, NY, USA (IBM 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 Excel		Yes (ODBC/flat files)	Yes (Excel/CSV input/output)
Load to/from Google Sheets			Yes (via Google Sheets plugin)
Two-Way Sync
dbt Core Integration
dbt Cloud Integration
OpenAPI / Developer API
G2 rating	4.8	4	4.1

Overview

IBM DataStage in Short

IBM DataStage (part of IBM InfoSphere Information Server) is a high-performance ETL and data integration platform that supports parallel processing and massive data volumes. It provides a visual design interface (DataStage Designer) to build data flows, along with features for metadata management, data lineage, and enterprise governance. DataStage can run on-premise or on cloud (via IBM Cloud Pak for Data) and integrates with IBM’s data quality and master data management solutions.

Pros

Parallel processing engine for high-throughput ETL, optimized for large data volumes.
Robust metadata management, data lineage, and governance via InfoSphere platform integration.
Supports on-premise, virtualized, and containerized (Cloud Pak) deployments for flexibility.
Extensive transformation library (data cleansing, lookups, joins) and connectivity (files, databases, mainframes, Hadoop).

Cons

High total cost of ownership: perpetual licensing and specialized administration needed.
User interface and development experience feel dated compared to modern cloud ETL tools.
Steep learning curve for job optimization (partitioning, parallel directives) and advanced features.

Reviews & Quotes

G2 Reviews:

What I like about IBM DataStage

“Best data integration tool on the market with a wide range of connectors and advanced data integration and quality features.”

What I dislike about IBM DataStage

“I quite like the platform as a whole, but I believe it can improve regarding data lineage (it should indeed improve now with the arrival of Manta to the IBM portfolio).”

Read full review

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.

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.”

Read full review

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.

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.”

Read full review

Feature-by-Feature Comparison

IBM DataStage

Pentaho Data Integration

Weld

Feature

IBM DataStage

Pentaho Data Integration

Weld

Ease of Use & Interface

Side-by-side

IBM DataStage

DataStage Designer provides a visual canvas to build ETL jobs, but the interface is relatively old-school. Job parameters, parallelism, and performance tuning require specialized training. Monitoring and debugging use InfoSphere consoles.

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.

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.

Ease of Use & Interface

Side-by-side

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.

Pricing & Affordability

Side-by-side

IBM DataStage

DataStage has high licensing costs (perpetual + support) and often requires dedicated hardware. Best suited for large enterprises with extensive ETL needs; cost-prohibitive for small/medium businesses.

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.

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.

Pricing & Affordability

Side-by-side

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.

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

IBM DataStage

Features include: visual job design, parallel processing (MPP), pushdown optimization (offloading to DB/Hadoop), data quality integration, metadata-driven development, and enterprise governance. Also supports REST and mainframe data sources.

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.

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.

Feature Set

Side-by-side

Flexibility & Customization

Side-by-side

IBM DataStage

Custom logic can be written via routines (BASIC, Java, or Python) and embedded in jobs. DataStage can integrate with external schedulers (Control M) and monitoring tools. However, it’s not open-source, so feature evolution is tied to IBM’s roadmap.

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.

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.