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
SAS Data Management
Score 8.0 out of 10
N/A
A suite of solutions for data connectivity, enhanced transformations and robust governance. Solutions provide a unified view of data with access to data across databases, data warehouses and data lakes. Connects with cloud platforms, on-premises systems and multicloud data sources.
N/A
Pricing
Azure Data Factory
SAS Data Management
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Azure Data Factory
SAS Data Management
Free Trial
No
No
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
—
—
More Pricing Information
Community Pulse
Azure Data Factory
SAS Data Management
Considered Both Products
Azure Data Factory
Verified User
Anonymous
Chose Azure Data Factory
Azure Data Factory fits well into our overall systems architecture where we already utilize largely Azure services and also Microsoft based products in the on-premises environment. I think cost structure is also very competitive with Azure Data Factory. Most services provide a …
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 …
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.
I'd chose data factory because its very easy to use, its UI is beautiful, it's library for .net is very useful and it lives within the microsoft ecosystem.
Azure Data Factory is a relatively new player in the space, and its feature set marks it as such. It does not have the full features of a more mature product set such as any of the above. However, it does allow for the creation of ETL/ELT flows/pipelines with minimal initial …
The product is best when combined with the other products of the SAS suite. In particular, it's great for the preparation, analysis and display of the data if it is carried out with the products indicated above. When it is combined with products other than those of the SAS …
SAS Data Management Platform requires third-party drivers to connect to common data sources like SFDC, MS SQL, Postgres. Has almost all features present as compared to the alternatives we evaluated. On top of it, SAS offered statistical transformations and strong metadata …
Because of ease of using SAS DI and data processing speed. There were lots of issues with AWS Redshift on cloud environment in terms of making connections with the data sources and while fetching the data we need to write complex queries.
Because SAS Data Integration Studio is the third party it seems to work equally well with all our systems. That is to say that it doesn't really work better with Microsoft or Oracle but really just seems to work equally well with all of them. It has a very powerful back-end …
Datastage might be the closest one. Being a full ETL tool, it's weird to compare both. Datastage might be more robust for extraction but it lacks the simplicity that the end users need for everyday data extract and analysis.
SAS/Access can work well with MySQL. There are some coding differences between the two, for example how missing values are handled or rules for variable names. MySQL has simpler coding, but if you are familiar with Base SAS, it is not too difficult to learn. With SAS/Access the …
SAS integration is not easy because there are various PAM related modules which require additional vendor involvement. Overall once all integrations are set up, it's a great tool and provides multiple options to users for running their model.
In a data pipeline, you will be able to add different kinds of activities for example connect from your on-premise SFTP and move CSV files to storage accounts. As well data factory has its own data flow if you are an ETL developer who experimented with maybe you have worked with SSIS, thus, you will start quickly with this new feature of the data factory.
SAS/Access is well suited for companies who need to manipulate and analyze large databases and data-sets. It does the same thing as SQL, and if you already know basic SAS coding it is easier to pick up. SAS/Access works well with analyzing data from multiple data-sources at once, including large databases stored in external and virtual environments like Hadoop. Data can be easily reassembled from relational databases for use by the user. SAS/Access is not necessary if you are only pulling data from one database that you have the physical file for.
SAS supports the main database connection options that allow you to optimize the performance of your extracts and loads.
Simplicity of the syntax for a basic connection.
Ability to configure by an administrator in a BI environment so that all users can benefit from the connection without having to establish it by themselves.
It is a versatile product but sometimes difficult to use due to the very close link with the proprietary programming language where specific knowledge is required.
Compared to competitors on the market that offer the same functions for the integration perimeter, it is certainly very expensive.
It is very simple to use when combined with products from the SAS suite, less so it is being used stand-alone or integrated with other well-known brands.
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 main negative point is the use of a non-standard language for customizations, as well as the poor integration with non-SAS systems. However, there is no doubt that it is a high-performance and powerful product capable of responding optimally to certain requirements.
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
With SAS, you pay a license fee annually to use this product. Support is incredible. You get what you pay for, whether it's SAS forums on the SAS support site, technical support tickets via email or phone calls, or example documentation. It's not open source. It's documented thoroughly, and it works.
Azure Data Factory fits well into our overall systems architecture where we already utilize largely Azure services and also Microsoft based products in the on-premises environment. I think cost structure is also very competitive with Azure Data Factory. Most services provide a visual interface for designing ETL workflows, but our team found Azure Data Factory's interface more intuitive.
Because SAS Data Integration Studio is the third party it seems to work equally well with all our systems. That is to say that it doesn't really work better with Microsoft or Oracle but really just seems to work equally well with all of them. It has a very powerful back-end that allows us to transform and load our data quickly and efficiently programmer time wise.