Comparing Azure Data Factory with Portable.io and Weld

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

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Weld vs Azure Data Factory vs Portable.io

	Weld	Azure Data Factory	Portable.io
Connectors	200+	90+	1000+
Price	$99 / 5M Active Rows	Pay per activity run + data movement; starts ~$0.25 per DIU-hour for data flows	Flat per connector (no volume fees)
Free tier
Location	EU	Azure 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 Excel		Yes (via REST connectors or staged files)
Load to/from Google Sheets
Two-Way Sync
dbt Core Integration
dbt Cloud Integration
OpenAPI / Developer API
G2 rating	4.8	4.4	4.8

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.

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.”

Read full review

Overview

Portable.io in Short

Portable.io is a cloud-based extract-and-load (EL) service specializing in “long-tail” connectors - niche APIs often overlooked by other ETL platforms. With over 1,000 pre-built connectors and on-demand custom connector development at no extra cost, it offers broad data source coverage. Portable focuses on extracting data and loading it into warehouses like Snowflake, BigQuery, and Redshift, leaving transformations to be done downstream. Its flat per-connector pricing ensures predictable costs, while managing API changes, rate limits, and errors for reliable, low-maintenance data pipelines—ideal for analytics teams needing easy access to niche data sources.

Pros

Unmatched connector breadth: 1,000+ connectors for niche and popular sources
On-demand custom connector development at no additional cost
Flat per-connector pricing; no volume-based fees
Fully managed - Portable handles API changes, schema updates, and pipeline maintenance
Set-and-forget simplicity with minimal configuration needed

Cons

EL-only (no in-platform transformations)
Cloud-only SaaS (no on-prem option)
No reverse ETL or activation features—it only loads to warehouses
Some new connectors may require initial tuning if usage is low until fully hardened
Limited scheduling granularity (mostly daily or on-demand syncs out of the box)

Reviews & Quotes

G2 Review:

What I like about Portable.io

“They have excellent support and communication in both timelines and quality of response.”

What I dislike about Portable.io

“There is a learning curve that can take some time to leverage more complex transformations and the support is limited with highly complex setups leaving some aspects of development more difficult.”

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

Azure Data Factory

Portable.io

Weld

Feature

Azure Data Factory

Portable.io

Weld

Ease of Use & Interface

Side-by-side

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.

Portable.io

Portable’s interface is minimalistic—users pick a source, enter credentials, and choose a destination. It’s extremely easy for non-technical users to onboard new connectors.

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

Portable’s interface is minimalistic—users pick a source, enter credentials, and choose a destination. It’s extremely easy for non-technical users to onboard new connectors.

Pricing & Affordability

Side-by-side

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.

Portable.io

Portable’s per-connector flat pricing makes costs predictable and often more affordable for companies with many small-volume sources, compared to volume-based models.

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

Portable’s per-connector flat pricing makes costs predictable and often more affordable for companies with many small-volume sources, compared to volume-based models.

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

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.

Portable.io

Focus on broad source coverage and reliability: over 1,000 connectors, incremental syncs, schema change handling, and managed maintenance. It does not provide transformations or reverse ETL, assuming those happen downstream.

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

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.

Portable.io

While there is no in-platform coding, Portable’s on-demand connector dev ensures virtually any source can be supported. Users trade transformation flexibility for maximum connector coverage and simplicity.

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.