Comparing Azure Data Factory with Skyvia and Weld

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

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Weld vs Azure Data Factory vs Skyvia

	Weld	Azure Data Factory	Skyvia
Connectors	200+	90+	70+
Price	$99 / 5M Active Rows	Pay per activity run + data movement; starts ~$0.25 per DIU-hour for data flows	Free (limited); paid plans from $15/month for 10k rows
Free tier
Location	EU	Azure Global (multi-region)	San Francisco, CA, USA
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)	Yes (CSV/Excel imports)
Load to/from Google Sheets
Two-Way Sync
dbt Core Integration
dbt Cloud Integration
OpenAPI / Developer API
G2 rating	4.8	4.4	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.

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

Skyvia in Short

Skyvia is a cloud-based data integration platform that lets users perform ETL, ELT, data replication, backup, and synchronization without coding. It supports over 190 data sources, including CRMs, marketing tools, cloud apps, and databases, and can load data into major cloud warehouses like Snowflake, BigQuery, Redshift, and Azure Synapse. With a browser-based interface, users can build and schedule data pipelines, automate workflows, and monitor tasks with detailed logging and alerts. Skyvia also offers backup and restore for cloud apps, visual SQL queries, and API publishing, making it a flexible, no-code solution for managing and integrating cloud data.

Pros

Fast, no-code setup for loading data from 70+ sources to warehouses or cloud DBs.
Handles incremental loads and can auto-detect schema changes for many sources.
Built-in data replication (one-way sync) and backup options for cloud data.
Free tier available (limited rows and sources) for basic usage.

Cons

No advanced transformation engine—only simple filters, mappings, and formula fields.
Pricing based on rows and connectors; high-volume loads can be costly.
Support and community resources are limited compared to major ETL vendors.

Reviews & Quotes

G2 Reviews:

What I like about Skyvia

“It just makes pulling Facebook Ads data into Snowflake so much smoother. The whole integration is pretty seamless: it's like we’ve got all our data in one spot now.”

What I dislike about Skyvia

“While Skyvia is powerful, sometimes more advanced transformation scenarios require workarounds or can't be fully implemented within the visual designer.”

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

Skyvia

Weld

Feature

Azure Data Factory

Skyvia

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.

Skyvia

Skyvia’s wizard-driven UI guides users through connecting source and destination, selecting objects, and scheduling. For basic use cases, it’s extremely quick. Complex pipelines aren’t its focus.

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

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.

Skyvia

Free tier allows up to 5000 rows/day. Paid plans start at $15/month for 10k rows plus $15 per additional 10k rows. For large-scale or continuous replication, costs scale accordingly.

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

Free tier allows up to 5000 rows/day. Paid plans start at $15/month for 10k rows plus $15 per additional 10k rows. For large-scale or continuous replication, costs scale accordingly.

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.

Skyvia

Supports: one-time or scheduled imports/exports, incremental loads (via key-based changes), data backup/restore, and firewall-friendly connectors. No transformations beyond mappings/filters.

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

Supports: one-time or scheduled imports/exports, incremental loads (via key-based changes), data backup/restore, and firewall-friendly connectors. No transformations beyond mappings/filters.

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.

Skyvia

Users can define simple formulas for fields (e.g., concatenation). For advanced transformations, they need external tools (e.g., dbt) after loading. No support for scripting within ETL.

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

Users can define simple formulas for fields (e.g., concatenation). For advanced transformations, they need external tools (e.g., dbt) after loading. No support for scripting within ETL.