Azure Data Factory vs. SAP Data Intelligence

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Azure Data Factory
Score 8.3 out of 10
N/A
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
SAP Data Intelligence
Score 8.5 out of 10
N/A
SAP Data Intelligence is presented by the vendor as a single solution to innovate with data. It provides data-driven innovation in the cloud, on premise, and through BYOL deployments. It is described by the vendor as the new evolution of the company's data orchestration and management solution running on Kubernetes, released by SAP in 2017 to deal with big data and complex data orchestration working across distributed landscapes and processing engine.N/A
Pricing
Azure Data FactorySAP Data Intelligence
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Azure Data FactorySAP Data Intelligence
Free Trial
NoYes
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoYes
Entry-level Setup FeeNo setup feeOptional
Additional Details
More Pricing Information
Community Pulse
Azure Data FactorySAP Data Intelligence
Considered Both Products
Azure Data Factory

No answer on this topic

SAP Data Intelligence
Chose SAP Data Intelligence
As we are implementing and using SAP 4HANA platform in other related projects, we have seen an advantage in utilizing SAP Data Intelligence. Also, with improved ETL pipelines and migration functionalities implemented, we have considered the financial aspect of the platform - …
Top Pros
Top Cons
Features
Azure Data FactorySAP Data Intelligence
Data Source Connection
Comparison of Data Source Connection features of Product A and Product B
Azure Data Factory
9.1
7 Ratings
10% above category average
SAP Data Intelligence
-
Ratings
Connect to traditional data sources9.27 Ratings00 Ratings
Connecto to Big Data and NoSQL9.07 Ratings00 Ratings
Data Transformations
Comparison of Data Transformations features of Product A and Product B
Azure Data Factory
8.5
7 Ratings
2% above category average
SAP Data Intelligence
-
Ratings
Simple transformations9.27 Ratings00 Ratings
Complex transformations7.77 Ratings00 Ratings
Data Modeling
Comparison of Data Modeling features of Product A and Product B
Azure Data Factory
7.7
7 Ratings
5% below category average
SAP Data Intelligence
-
Ratings
Data model creation8.35 Ratings00 Ratings
Metadata management7.56 Ratings00 Ratings
Business rules and workflow7.57 Ratings00 Ratings
Collaboration7.06 Ratings00 Ratings
Testing and debugging7.57 Ratings00 Ratings
Data Governance
Comparison of Data Governance features of Product A and Product B
Azure Data Factory
7.7
7 Ratings
6% below category average
SAP Data Intelligence
-
Ratings
Integration with data quality tools7.47 Ratings00 Ratings
Integration with MDM tools8.07 Ratings00 Ratings
Best Alternatives
Azure Data FactorySAP Data Intelligence
Small Businesses
Skyvia
Skyvia
Score 9.6 out of 10

No answers on this topic

Medium-sized Companies
IBM InfoSphere Information Server
IBM InfoSphere Information Server
Score 8.1 out of 10

No answers on this topic

Enterprises
IBM InfoSphere Information Server
IBM InfoSphere Information Server
Score 8.1 out of 10
Talend Data Fabric
Talend Data Fabric
Score 9.4 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Azure Data FactorySAP Data Intelligence
Likelihood to Recommend
9.3
(7 ratings)
8.1
(54 ratings)
Likelihood to Renew
-
(0 ratings)
8.2
(2 ratings)
Usability
-
(0 ratings)
7.1
(49 ratings)
Support Rating
7.0
(1 ratings)
7.2
(46 ratings)
Configurability
-
(0 ratings)
8.2
(1 ratings)
Vendor post-sale
-
(0 ratings)
9.1
(1 ratings)
Vendor pre-sale
-
(0 ratings)
9.1
(1 ratings)
User Testimonials
Azure Data FactorySAP Data Intelligence
Likelihood to Recommend
Microsoft
Well-suited Scenarios for Azure Data Factory (ADF): When an organization has data sources spread across on-premises databases and cloud storage solutions, I think Azure Data Factory is excellent for integrating these sources. Azure Data Factory's integration with Azure Databricks allows it to handle large-scale data transformations effectively, leveraging the power of distributed processing. For regular ETL or ELT processes that need to run at specific intervals (daily, weekly, etc.), I think Azure Data Factory's scheduling capabilities are very handy. Less Appropriate Scenarios for Azure Data Factory: Real-time Data Streaming - Azure Data Factory is primarily batch-oriented. Simple Data Copy Tasks - For straightforward data copy tasks without the need for transformation or complex workflows, in my opinion, using Azure Data Factory might be overkill; simpler tools or scripts could suffice. Advanced Data Science Workflows: While Azure Data Factory can handle data prep and transformation, in my experience, it's not designed for in-depth data science tasks. I think for advanced analytics, machine learning, or statistical modeling, integration with specialized tools would be necessary.
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SAP
It helps our BUs analyze data and create dashboards they can understand. While slowing down with a large database, it becomes less helpful. In my experience, it is excellent in consolidating information from several sources for analysis, decision-making, and knowledge gaps. Excellent at managing information access.
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Pros
Microsoft
  • It allows copying data from various types of data sources like on-premise files, Azure Database, Excel, JSON, Azure Synapse, API, etc. to the desired destination.
  • We can use linked service in multiple pipeline/data load.
  • It also allows the running of SSIS & SSMS packages which makes it an easy-to-use ETL & ELT tool.
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SAP
  • It integrates well with our current ecosystem of SAP products, like HANA.
  • It provides end-to-end machine learning operations, with tools for the complete model life cycle.
  • It has a simple user interface for novice users, with complex tools also available for power users.
  • It builds on SAP Data Hub, providing all the ETL functions of that tool with additional machine learning functionality.
  • It can run in the cloud, no on-premise software management needed.
  • Many programming languages are supported, it provides a sandbox environment for the user to develop in whichever style they prefer.
  • SAP is very actively developing and improving it.
Read full review
Cons
Microsoft
  • Limited source/sink (target) connectors depending on which area of Azure Data Factory you are using.
  • Does not yet have parity with SSIS as far as the transforms available.
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SAP
  • Data transfer speed tends to be slow when there is poor internet connection since SAP Data Intelligence don’t synchronize data while offline. However, this is not vendor fault, that’s why we have implemented robust wireless technology internet connection in our organization.
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Likelihood to Renew
Microsoft
No answers on this topic
SAP
Allow collaborations among various personas
with insights as ratings and comments on the
datasets Reuse knowledges on the datasets for new users Next-Gen Data Management and Artificial Intelligence
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Usability
Microsoft
No answers on this topic
SAP
Good tool with lots of potential, but I still see a lot of room for improvement, e.g. when it comes to debugging functionality to understand exactly where pipelines fail and what the data at that point looks like (similar to BW debugging). Also, I am missing SAPs standard machine learning libraries (Python) to be pre-installed, among some other general usability improvements.
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Support Rating
Microsoft
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
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SAP
Initially we struggle to get help from SAP but then dedicated Dev angel was assigned to us and that simplify the overall support scenario. There is still room of improvement in documentation around SAP Data intelligence. We struggle a lot to initially understand the feature and required help around performance improvement area,
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Alternatives Considered
Microsoft
The easy integration with other Microsoft software as well as high processing speed, very flexible cost, and high level of security of Microsoft Azure products and services stack up against other similar products.
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SAP
One of the reasons to pick SAP Data Intelligence is the speed and security it provides, in addition to the excellent support it provides. It is also compatible with all popular databases, which is another reason to choose it.
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Return on Investment
Microsoft
  • It is very useful and make things easier
  • Debugging can improve
  • Its better suited than other products with the same objective
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SAP
  • Automation of data management slashed tasks by over 60% in most departments for the first 8 months.
  • Metadata catalogs have enabled us to categorize data from disjointed sources in one place.
  • It runs multiple ML models which enhances flexibility when managing data.
Read full review
ScreenShots

SAP Data Intelligence Screenshots

Screenshot of Business GlossaryScreenshot of Example of data quality operatorsScreenshot of Data profiling fact sheetScreenshot of SAP Data Intelligence Jupyter lab notebook for machine learningScreenshot of SAP Data Intelligence data pipeline using PythonScreenshot of SAP Data Intelligence example ata quality dashboard