Microsoft's Azure Data Factory is a service built for all data integration needs and skill levels. It is designed to allow the user to easily construct ETL and ELT processes code-free within the intuitive visual environment, or write one's own code. Visually integrate data sources using more than 80 natively built and maintenance-free connectors at no added cost. Focus on data—the serverless integration service does the rest.
N/A
Zapier
Score 8.9 out of 10
N/A
The Zapier Automation Platform designed to integrate data between web apps. It is scaled for small to mid-sized businesses, with a functional but limited free version of the program.
$29.99
per month 750 tasks per month
Pricing
Azure Data Factory
Zapier
Editions & Modules
No answers on this topic
Starter
$29.99
per month 750 tasks per month
Professional
$73.50
per month 2k tasks per month
Team
$103.50
per month 2k tasks per month
Company
Contact Sales
Offerings
Pricing Offerings
Azure Data Factory
Zapier
Free Trial
No
No
Free/Freemium Version
No
Yes
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
—
33% discount for annual pricing.
More Pricing Information
Community Pulse
Azure Data Factory
Zapier
Features
Azure Data Factory
Zapier
Data Source Connection
Comparison of Data Source Connection features of Product A and Product B
Azure Data Factory
8.5
10 Ratings
3% above category average
Zapier
-
Ratings
Connect to traditional data sources
9.010 Ratings
00 Ratings
Connecto to Big Data and NoSQL
8.010 Ratings
00 Ratings
Data Transformations
Comparison of Data Transformations features of Product A and Product B
Azure Data Factory
7.8
10 Ratings
3% below category average
Zapier
-
Ratings
Simple transformations
8.710 Ratings
00 Ratings
Complex transformations
7.010 Ratings
00 Ratings
Data Modeling
Comparison of Data Modeling features of Product A and Product B
Azure Data Factory
6.3
10 Ratings
21% below category average
Zapier
-
Ratings
Data model creation
4.57 Ratings
00 Ratings
Metadata management
5.58 Ratings
00 Ratings
Business rules and workflow
6.010 Ratings
00 Ratings
Collaboration
7.09 Ratings
00 Ratings
Testing and debugging
6.310 Ratings
00 Ratings
Data Governance
Comparison of Data Governance features of Product A and Product B
Azure Data Factory
5.7
10 Ratings
33% below category average
Zapier
-
Ratings
Integration with data quality tools
4.310 Ratings
00 Ratings
Integration with MDM tools
7.09 Ratings
00 Ratings
Cloud Data Integration
Comparison of Cloud Data Integration features of Product A and Product B
Best scenario is for ETL process. The flexibility and connectivity is outstanding. For our environment, SAP data connectivity with Azure Data Factory offers very limited features compared to SAP Data Sphere. Due to the limited modelling capacity of the tool, we use Databricks for data modelling and cleaning. Usage of multiple tools could have been avoided if adf has modelling capabilities.
If you have processes that are now managed and controlled using a spreadsheet, Zapier will give you a lot more control over what is happening and will help you increase productivity by eliminating simple steps such as sending emails and sharing information with your colleagues. It frees time for very transactional activities.
Ease of use - multiple people in the organization can set up and run Zaps per their specific use cases without much training.
Connectivity - Zapier is able to connect to multiple applications we use on a regular basis.
Functionality - Zapier provides embedded functionality within the app itself (email, data conversion), but also appropriate triggers and actions for apps it connects to.
Versatile - Zapier can execute complicated and simple tasks and thus has many use cases.
Granularity of Errors: Sometimes, Azure Data Factory provides error messages that are too generic or vague for us, making it challenging to pinpoint the exact cause of a pipeline failure. Enhanced error messages with more actionable details would greatly assist us as users in debugging their pipelines.
Pipeline Design UI: In my experience, the visual interface for designing pipelines, especially when dealing with complex workflows or numerous activities, can become cluttered. I think a more intuitive and scalable design interface would improve usability. In my opinion, features like zoom, better alignment tools, or grouping capabilities could make managing intricate designs more manageable.
Native Support: While Azure Data Factory does support incremental data loads, in my experience, the setup can be somewhat manual and complex. I think native and more straightforward support for Change Data Capture, especially from popular databases, would simplify the process of capturing and processing only the changed data, making regular data updates more efficient
So far product has performed as expected. We were noticing some performance issues, but they were largely Synapse related. This has led to a shift from Synapse to Databricks. Overall this has delayed our analytic platform. Once databricks becomes fully operational, Azure Data Factory will be critical to our environment and future success.
The interface is very user-friendly, and there are also many tools to help a brand-new user get started. For example, you can put your Zap idea into the AI bot, and it will basically build a shell of your Zap to get started on. The format for each step within a Zap is also very helpful (set up the connection/app, set up the fields/details, then test).
We have not had need to engage with Microsoft much on Azure Data Factory, but they have been responsive and helpful when needed. This being said, we have not had a major emergency or outage requiring their intervention. The score of seven is a representation that they have done well for now, but have not proved out their support for a significant issue
Before we purchased Zapier, I contacted support and asked them if Zapier could support my intended workflow (this is actually a selection on their support form - awesome). Within 2 hours, I was contacted by a support team member who seemed sure it would work, but granted me premium access for 2 weeks to try it out for myself. Sure enough, it did! Ever since then, support has replied rapidly to any problems I have experienced and answered my questions within a few sentences.
Azure Data Factory helps us automate to schedule jobs as per customer demands to make ETL triggers when the need arises. Anyone can define the workflow with the Azure Data Factory UI designer tool and easily test the systems. It helped us automate the same workflow with programming languages like Python or automation tools like ansible. Numerous options for connectivity be it a database or storage account helps us move data transfer to the cloud or on-premise systems.
We actually utilize both Integromat and Zapier at our company, for all the reasons detailed in this review. Though Zapier is excellent for simple client integrations, we often run into internal use cases that require complexity that Zapier cannot provide. Specifically working with API calls (not just webhooks), complex multi-step integrations with Routing/parsing/etc, and large volume integrations. Integromat is perfect for these use cases, but doesn’t provide the simplicity and account scalability that Zapier offers.