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Comparing Azure Data Factory with Rows.com and Weld

You’re comparing Azure Data Factory vs Rows.com vs Weld. Explore how they differ on connectors, pricing, and features. Ed Logo

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Weld vs Azure Data Factory vs Rows.com

WeldAzure Data FactoryRows.com
Connectors200+90+
Price$99 / 5M Active RowsPay per activity run + data movement; starts ~$0.25 per DIU-hour for data flowsFree / starts at $39/user/mo for Pro
Free tier
LocationEUAzure Global (multi-region)US
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 REST connectors or staged files)
Load to/from Google Sheets
Two-Way Sync
dbt Core Integration
dbt Cloud Integration
OpenAPI / Developer API
G2 rating4.84.4

Overview

Azure Data Factory in Short

Azure Data Factory (ADF) is Microsoft’s cloud-based data integration service for creating ETL/ELT pipelines. ADF supports a drag-and-drop pipeline designer, over 90 built-in connectors for Azure, on-premises, and SaaS data sources, and can execute transformations via Azure Databricks, U-SQL, or stored procedures. It also includes features for data orchestration, monitoring, and hybrid data integration scenarios.

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Pros

  • 90+ built-in connectors (Azure SQL, Cosmos DB, SAP, Oracle, Salesforce, etc.) and support for custom REST endpoints.

  • Visual pipeline orchestration with debug, parameterization, and Git integration for CI/CD.

  • Hybrid data integration via Self-hosted Integration Runtime for on-premises sources.

  • Integration with Azure Synapse, Databricks, and Azure Functions for flexible transformation and compute.

Cons

  • Complex pricing: charges per pipeline activity, per DIU for data flows, and for data movement across regions.

  • UI can be slow when working with large pipelines; error messages are often generic, requiring deeper investigation.

  • Steeper learning curve for advanced features (e.g., mapping data flows with Spark under the hood).

Reviews & Quotes

Gartner Peer Review:

What I like about Azure Data Factory

Its flexibiliity in connecting diverse data sources and integration with the Azure ecosystem are standout advantages.

What I dislike about Azure Data Factory

Some features are too rigid. Lack of detailed error messages can plague a workstream during setup.

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.

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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.

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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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Azure Data Factory

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Rows.com

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Weld

Ease of Use & Interface

Side-by-side

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Azure Data Factory

ADF’s UI provides a canvas for building pipelines and data flows. Basic data movement is intuitive, but advanced mapping data flows (visual Spark transformations) require understanding Spark concepts. Integration with Git makes collaboration easier.

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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.

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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

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Azure Data Factory

ADF charges per pipeline activity (at least $0.25/activity), per DIU-hour for data flows, plus data movement costs (e.g., $0.25/GB). Estimating costs can be tricky due to these components, but pay-as-you-go avoids upfront fees.

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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.

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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

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Azure Data Factory

Features include: pipeline orchestration, mapping data flows (visual Spark jobs), hybrid integration via self-hosted runtime, triggers (schedule, event, tumbling window), monitoring & alerting, and integration with Azure Monitor. Also supports SSIS lift-and-shift for on-prem ETL workloads.

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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.

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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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Azure Data Factory

ADF allows custom .NET activities, Azure Functions, and Databricks notebooks within pipelines. It supports parameterized templates, branching, and custom Azure ML scoring steps. However, customization often requires familiarity with other Azure services.

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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.

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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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