

SAS Data Management and Azure Data Factory are prominent competitors in the data management and integration sector. Azure Data Factory appears to have the upper hand due to its seamless integration with Azure services and user-friendly interface, despite potential improvements in other areas.
Features: SAS Data Management stands out for its comprehensive data quality and integration capabilities, providing a unified view of enterprise data and accommodating multiple data sources. It also excels in reporting and customization. Azure Data Factory offers robust ETL functionalities with a user-friendly visual interface, highlighting its drag-and-drop feature for data workflows. It provides flexibility and scalability with built-in connectors for diverse sources.
Room for Improvement: SAS Data Management is often criticized for its high cost with a complex licensing model. Connectivity issues requiring third-party solutions and limited integration flexibility are noted drawbacks, coupled with a need for better documentation and simplified installation. Azure Data Factory could enhance its complex pricing model, real-time processing capabilities, and some missing connectors. Its integration and support for streaming data are also areas that require significant improvement, along with performance and UI enhancements.
Ease of Deployment and Customer Service: SAS Data Management primarily runs on-premises and is noted for its reliable customer service, although the support knowledge base is sometimes seen as lacking. Azure Data Factory, leveraging cloud deployments, provides great flexibility and scalability, although it faces mixed reviews in customer service responsiveness and technical support depth.
Pricing and ROI: SAS Data Management is seen as expensive with a complex pricing structure, yet offers significant ROI in sectors requiring compliance. The investment is justified by its integration and data standardization capabilities. Azure Data Factory operates on a pay-as-you-go model that offers flexibility but can lead to high costs if not managed well. Its competitive pricing makes it accessible to various businesses and tends to yield favorable ROI due to efficient data processing, despite a complex pricing estimation.
Our stakeholders and clients have expressed satisfaction with Azure Data Factory's efficiency and cost-effectiveness.
Reliable data plus less human intervention and less error result in a strong return on investment.
On a scale of one to ten, I would rate the technical support as nine.
The technical support from Microsoft is rated an eight out of ten.
The technical support is responsive and helpful
The support for SAS in Brazil is not the best one, but the support in Sweden is really good, as they visit the company and work to solve the issues.
Azure Data Factory is highly scalable.
I did not experience scalability issues.
The solution has a high level of stability, roughly a nine out of ten.
I have been using Azure Data Factory for a very long time, and I did not find too many issues.
The ability to handle the largest volumes of data is another concern; if I have to manage more than one terabyte of data every day, I am not comfortable dealing with Azure Data Factory and had to switch to Oracle Data Integrators (ODI) because it lacks performance features.
Incorporating more dedicated API sources to specific services like HubSpot CRM or Salesforce would be beneficial.
Sometimes, the compute fails to process data if there is a heavy load suddenly, and it doesn't scale up automatically.
There is significant room for improvement, especially with regard to using a hybrid approach that involves both CAS and persistent storage.
SAS Data Management can be improved in terms of the learning curve.
The pricing is cost-effective.
It is considered cost-effective.
From my experience, SAS Data Management is an expensive tool.
It connects to different sources out-of-the-box, making integration much easier.
The platform excels in handling major datasets, particularly when working with Power BI for reporting purposes.
Regarding the integration feature in Azure Data Factory, the integration part is excellent; we have major source connectors, so we can integrate the data from different data sources and also perform basic transformation while transforming, which is a great feature in Azure Data Factory.
SAS Data Management stands out because of its data standardization, transformation, and verification capabilities.
The best features I appreciate about SAS Data Management tool are that it's easy to create the flows and schedule data, and the tables are not too big, making it easy to control the ETL process, including user access which is also easy to manage in SAS.
SAS Data Management's best feature is first, data reliability because SAS Data Management is a very trusted platform.
| Product | Mindshare (%) |
|---|---|
| Azure Data Factory | 2.3% |
| SAS Data Management | 1.2% |
| Other | 96.5% |


| Company Size | Count |
|---|---|
| Small Business | 31 |
| Midsize Enterprise | 21 |
| Large Enterprise | 63 |
| Company Size | Count |
|---|---|
| Small Business | 8 |
| Midsize Enterprise | 2 |
| Large Enterprise | 8 |
Azure Data Factory efficiently manages and integrates data from various sources, enabling seamless movement and transformation across platforms. Its valuable features include seamless integration with Azure services, handling large data volumes, flexible transformation, user-friendly interface, extensive connectors, and scalability. Users have experienced improved team performance, workflow simplification, enhanced collaboration, streamlined processes, and boosted productivity.
SAS Data Management provides data integration, governance, and robust reporting tools. It connects to diverse data sources, ensuring quality management and enabling data analysis for technical and non-technical users.
SAS Data Management features flexible data flow creation, scheduling, and ETL control. It enhances data integration and metadata management with tools that support data standardization. Users benefit from its importing and exporting capabilities, connecting to multiple sources. It facilitates improved data quality management and offers a flexible language for diverse needs. Data visualization capabilities further support decision-making across industries, automating reports and data warehouses.
What are the key features of SAS Data Management?SAS Data Management helps industries like finance integrate diverse data sources for analytics and reporting. It is used for tasks such as financial reporting, credit risk analysis, and data cleansing. Through user-driven automation, it aids in aligning data warehouses and generating insightful visual outputs, making it ideal for analyzing structured data from sources like Excel and CSV files.
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