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.”
Comparing IBM DataStage with Rows.com and Weld
You’re comparing IBM DataStage vs Rows.com vs Weld. Explore how they differ on connectors, pricing, and features. 
Loved by data teams from around the world
Weld vs IBM DataStage vs Rows.com
| Weld | IBM DataStage | Rows.com | |
|---|---|---|---|
| Connectors | 200+ | 200+ | — |
| Price | $99 / 5M Active Rows | Enterprise licensing (custom, usually six-figure annual) | Free / starts at $39/user/mo for Pro |
| Free tier | |||
| Location | EU | Armonk, NY, USA (IBM HQ) | US |
| 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) | ||
| Load to/from Google Sheets | |||
| Two-Way Sync | |||
| dbt Core Integration | |||
| dbt Cloud Integration | |||
| OpenAPI / Developer API | |||
| G2 rating | 4.8 | 4 | — |
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 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).”
Overview
Rows.com in Short
Rows.com is a next-generation spreadsheet platform that natively integrates with hundreds of SaaS APIs, databases, and BI tools. It automates data imports (ELT) directly into your spreadsheet, lets you build dashboards and reports, and supports scripting and automation—all inside a familiar spreadsheet interface.
Pros
Native connectors to 500+ SaaS tools (partnerships with major APIs)
Automates ELT directly into the spreadsheet—no separate pipeline to maintain
Built-in charting, collaboration, and dashboard capabilities
Supports JavaScript and Python formulas for advanced automation
Free plan available with core features
Cons
Heavy API-dependent sheets can lag when importing large datasets
Some enterprise connectors and advanced automations require paid plans
Not designed for full data-warehouse scale—best for mid-size data tables
Reviews & Quotes
Rows.com review on G2:
What I like about Rows.com
“Creating tables from Excel or Google Sheets imports is incredible. Creating charts and visuals in just a few clicks and navigating your workspace is PERFECT.”
What I dislike about Rows.com
“The basic dashboard is not very clear. Need to understand the features and divide screens to jump between spaces.”
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
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
IBM DataStage
Rows.com
Weld
Feature
IBM DataStage
Rows.com
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.
Rows.com
Rows.com feels like a modern spreadsheet but with built-in API connectors. Non-technical users can browse pre-built integrations, while power users can script custom workflows in JavaScript or Python.
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
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.
Rows.com feels like a modern spreadsheet but with built-in API connectors. Non-technical users can browse pre-built integrations, while power users can script custom workflows in JavaScript or Python.
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
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.
Rows.com
A free tier covers most basic import needs. Paid plans start at $39/user/month for Pro, which unlocks advanced integrations, higher API quotas, and dedicated support. Enterprise pricing is custom.
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
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.
A free tier covers most basic import needs. Paid plans start at $39/user/month for Pro, which unlocks advanced integrations, higher API quotas, and dedicated support. Enterprise pricing is custom.
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.
Rows.com
Rows.com offers ELT connectors, in-sheet data transformations (via formulas or scripts), scheduling/automation, native charting and dashboards, real-time collaboration, and Jira/Slack notifications. It bridges spreadsheet flexibility with ETL and BI tooling.
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
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.
Rows.com offers ELT connectors, in-sheet data transformations (via formulas or scripts), scheduling/automation, native charting and dashboards, real-time collaboration, and Jira/Slack notifications. It bridges spreadsheet flexibility with ETL and BI tooling.
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
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.
Rows.com
Users can write custom JavaScript/Python functions directly in cells, chain API calls across sheets, and build automated workflows (e.g., “every morning, pull this data and send a Slack alert”). It’s highly customizable for spreadsheet-centric data work.
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.
Flexibility & Customization
Side-by-side
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.
Users can write custom JavaScript/Python functions directly in cells, chain API calls across sheets, and build automated workflows (e.g., “every morning, pull this data and send a Slack alert”). It’s highly customizable for spreadsheet-centric data work.
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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