Comparing Azure Data Factory with Hevo and Weld



What is Azure Data Factory
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).
Azure Data Factory Documentation:
What I like about Azure Data Factory
ADF’s visual pipeline authoring and integration with other Azure services (Databricks, Synapse) make it easy to build end-to-end data workflows without managing infrastructure.
What I dislike about Azure Data Factory
Pricing is multifaceted (per activity run, data movement, SSIS integration), which can be hard to forecast. Debugging pipeline errors often requires sifting through activity logs.
What is Hevo
Pros
- Supports both ELT, ELT, and reserve ELT
- Plenty of fully maintained connectors
- Great for non-technical users
- Simple UI that's easy to work with
- Affordable pricing
Cons
- Limited features for more advanced use cases
- Limited custom scheduling features
- Only 50 connectors are available on the Free plan
- Lack of flexibility when wanting to edit pipelines
- Error messages and status codes could be better
As one reviewer on G2 puts it: :
What I like about Hevo
Hevo is really good for normal pipelines, but it has some limitations for more complex use cases.
What I dislike about Hevo
What is Weld
Pros
- Premium quality connectors and reliability
- User-friendly and easy to set up
- AI assistant
- Very competitive and easy-to-understand pricing model
- Reverse ETL option
- Lineage, orchestration, and workflow features
- Advanced transformation and SQL modeling capabilities
- Ability to handle large datasets and near real-time data sync
- Combines data from a wide range of sources for a single source of truth
Cons
- Requires some technical knowledge around data warehousing and SQL
- Limited features for advanced data teams
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.
Azure Data Factory vs Hevo: Ease of Use and User Interface
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.
Hevo
Hevo is designed with non-technical users in mind, offering a simple UI and code-free capabilities, making it easy for beginners to use.
Azure Data Factory vs Hevo: Pricing Transparency and Affordability
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.
Hevo
Hevo offers affordable pricing and a free plan with limited connectors, making it accessible for startups and small businesses. However, the costs can rise with data volume and feature needs.
Azure Data Factory vs Hevo: Comprehensive Feature Set
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.
Hevo
Hevo supports ETL, ELT, and reverse-ETL, making it versatile for different data needs. It also has plenty of fully maintained connectors, although it may lack some advanced features required by seasoned data professionals.
Azure Data Factory vs Hevo: Flexibility and Customization
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.
Hevo
While Hevo is great for non-technical users, it lacks flexibility and customization options for more complex data tasks, making it less suitable for advanced data teams.
Summary of Azure Data Factory vs Hevo vs Weld
Weld | Azure Data Factory | Hevo | |
---|---|---|---|
Connectors | 200++ | 90+ | 150+ |
Price | $99 / Unlimited usage | Pay per activity run + data movement; starts ~$0.25 per DIU-hour for data flows | $299 / 5M rows |
Free tier | No | Yes | Yes |
Location | EU | Azure Global (multi-region) | INDIA |
Extract data (ETL) | Yes | Yes | Yes |
Sync data to HubSpot, Salesforce, Klaviyo, Excel etc. (reverse ETL) | Yes | No | Yes |
Transformations | Yes | Yes | Yes |
AI Assistant | Yes | No | No |
On-Premise | No | No | No |
Orchestration | Yes | Yes | No |
Lineage | Yes | Yes | No |
Version control | Yes | Yes | No |
Load data to and from Excel | Yes | Yes | No |
Load data to and from Google Sheets | Yes | No | No |
Two-Way Sync | Yes | No | No |
dbt Core Integration | Yes | No | Yes |
dbt Cloud Integration | Yes | No | No |
OpenAPI / Developer API | Yes | No | Yes |
G2 Rating | 4.8 | 4.4 | 4.3 |
Conclusion
You’re comparing Azure Data Factory, Hevo, Weld. Each of these tools has its own strengths:
- 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. . 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. .
- Hevo: hevo supports etl, elt, and reverse-etl, making it versatile for different data needs. it also has plenty of fully maintained connectors, although it may lack some advanced features required by seasoned data professionals.. hevo offers affordable pricing and a free plan with limited connectors, making it accessible for startups and small businesses. however, the costs can rise with data volume and feature needs..
- 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.. weld offers a straightforward and competitive pricing model, starting at $99 for 2 million active rows, making it more affordable and predictable, especially for small to medium-sized enterprises..