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Comparing Azure Data Factory with Matillion and Weld

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

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Weld vs Azure Data Factory vs Matillion

WeldAzure Data FactoryMatillion
Connectors200+90+110+
Price$99 / 5M Active RowsPay per activity run + data movement; starts ~$0.25 per DIU-hour for data flows$2.00 per credit
Free tier
LocationEUAzure Global (multi-region)UK
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 rating4.84.44.3

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

Matillion in Short

Matillion is a cloud-native data integration platform that enables enterprises to build and manage ETL/ELT pipelines using a low-code, visual interface. Designed for cloud data warehouses like Snowflake, Redshift, and BigQuery, it allows users to extract, transform, and load data from various sources efficiently. With strong scheduling, orchestration, and monitoring features, Matillion is well-suited for handling complex workflows and large-scale data transformation needs.

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Pros

  • Large number of connectors

  • Robust feature set

  • Lots of advanced features for larger enterprises and data teams

  • Has both ELT and ETL capabilities

  • On premise options

Cons

  • Expensive for small businesses

  • Steep learning curve for non-technical users

  • Requires a large upfront investment and implementation

Reviews & Quotes

A reviewer on G2 said::

What I like about Matillion

Built-in connectors to heaps of systems; ability to create custom connectors; active community and quick responses to forum questions

What I dislike about Matillion

Some components are a bit clunky; cloud version is not mature and lacks some features from the server-based version

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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Matillion

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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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Matillion

Matillion has a steep learning curve, especially for non-technical users, due to its robust feature set and advanced capabilities designed for larger enterprises.

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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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Matillion

Matillion's pricing can be expensive, particularly for small businesses, as it is based on credits and requires a significant upfront investment.

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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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Matillion

Matillion offers a robust set of features with support for both ETL and ELT, along with numerous connectors and on-premise options, making it ideal for large enterprises with complex data needs.

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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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Matillion

Matillion provides extensive customization and flexibility options, particularly for large enterprises, but may be overkill for smaller teams or simpler use cases.

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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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