Azure Data Factory Reviews

We are using this solution to gather information from SCADA systems, analyze it using AI and machine learning, and then sending the results to our users. They receive and view the data using the Power BI interface.

The integration with the whole environment is smooth and transparent.

The reason that we implemented this product is for the full integration with the whole Azure environment. It is very important because you don't have to deal with security, identity flow, or audit flow.

The security of the agent that is installed on-premises is very good. This is another important feature for us.

It comes with a lot of connectors out of the box, including support for SQL, Oracle, SAP, and ODBC.

The pricing scheme is very complex and difficult to understand. Analyzing it upfront is impossible, so we just decided to start using it and figure out the costs on a weekly or monthly basis.

We have just begun using Azure Data Factory within the past two or three months and it is not fully rolled out yet.

We have no issues with technical support. We are working closely with Microsoft partners. There were a couple of problems during the installation that were solved on the fly, and otherwise, we haven't had and trouble.

We started with iConduct and as we migrated to the Azure environment, we began the process of switching to the Microsoft Azure Data Factory.

The initial setup was not very complex and the deployment was very quick. We were set up within a matter of days, or perhaps a week.

We received help from one of the Microsoft partners, who handled the installation for us.

To this point, we are still learning the system and have only tried a very simple data flow. At this point, we haven't had any issues.

I would rate this solution an eight out of ten.

The use cases are more related to logistics, our finance, and back-office activity.  

The most valuable part of this product is the ease of use. It is easy to use and rather intuitive. Because it is easy to use, you can do things with it easily. The more things make your work easy, the more valuable they are.  

Because I have not really done a really deep benchmark against competitors, I may not be familiar enough with the potential of competing products and capabilities to be able able to say what is missing or should be improved definitively.  

From my perspective, the pricing seems like it could be more user-friendly. Of course, nothing is ever as inexpensive as you want.  

Perhaps one good additional feature would be incorporating more ways to import and export data. It would be nice to have the product fit our service orchestration platform better to make the transfer more fluid.  

We started using this product a year ago.  

The stability of the product is good.  

The scalability seems okay. As we have only been using it for a short time, it is hard to say more. We are not currently planning to scale usage dramatically at this point but of course we would like to grow. On a scale from one to ten and from what I know, I would say scalability is an eight-out-of-ten. I can't be sure exactly how many people are using the system, but we have hundreds of thousands of users currently. Internally, I would say we use the product often.  

I have not had a reason to be in touch with technical support, but I don't know whether others in the organization have been in touch with them. As far as I know, there has been no reason to be.  

The initial setup was not simple and it was not complex. It was in the middle.  

I would say it took two months for the deployment.  

We have a department of developers that implemented the product. The deployment happened before I joined the organization.  

The advice I would give to someone who is looking to implement this product is to understand the IT technology of the product first and why it would be needed. That is the point where you have to start. Next, you have to understand if the product itself fits your organizational needs. That is you have to look at the business requirements and see whether the product really fits the organization and solves the problems while conforming to the business model.  

On a scale from one to ten where one is the worst and ten is the best, I would rate the product overall as an eight-out-of-ten.  

I primarily use Data Factory for data ingestion and B2B transformation.

Data Factory's best features are connectivity with different tools and focusing data ingestion using pipeline copy data.

Data Factory's monitorability could be better. In the next release, Data Factory should include integrations with open-source tools like Air Flow.

I've been working with Data Factory for about a year.

Data Factory is stable.

Data Factory is scalable.

Microsoft's technical support is good, so long as your company has a good relationship with them.

I previously worked with Talend, Matillion, and Fivetran.

Data Factory is expensive.

I would rate Data Factory seven out of ten.

We mainly use this solution to carry out data movement and transformation.

This solution has provided us with an easier, and more efficient way to carry out data migration tasks.

This solution is currently only useful for basic data movement and file extractions, which we would like to see developed to handle more complex data transformations.

We have been using this solution for a year.

We have found this to be a stable solution.

This is an easily scalable product, due to it being cloud-based.

The customer support for this solution is very good. 

The initial setup of this product is straightforward, if you deploy the solution using a template; rather than implementing the solution first, and configuring the features afterwards.

We implemented the product using both in-house staff, and members of a vendor team. The vendor team were very helpful, and gave good advice while we were deploying the solution.

We would recommend this solution as it is very solid and has good security features.

I would rate this solution an eight out of 10.

We are currently using it as an ETL (Extract, Transform, and Load) tool. We are using it to connect to various information providers or, in general, to various sources, to extract data, and then to insert it to our storage devices, databases, or data warehouses.

The two most valuable features of Azure Data Factory are that it's very scalable and that it's also highly reliable.

One area for improvement is documentation. At present, there isn't enough documentation on how to use Azure Data Factory in certain conditions. It would be good to have documentation on the various use cases.

Sometimes, it's really difficult to find the answers to very technical questions regarding certain conditions.

I've been using Azure Data Factory since 2019.

It has been stable so far.  

Azure Data Factory is a very scalable solution. Including internal developers and external consultants working for us, we have about 10-15 people using this solution.

We had been using various ETL tools during the years before moving to the cloud. We picked Azure Data Factory because we were moving towards the Azure cloud.

The initial setup is very easy.

We used a consultant as it was a big project. We had five to six specialists, including both internal and external employees, working on it. It took about about three to six months to complete.

Azure Data Factory is a very easy to use tool. If you want to extract, manipulate, and load data to any type of Azure repository, I recommend this solution. However, I would not recommend it if the manipulation of data is very deep and complicated.

I would rate this solution at eight on a scale from one to ten.

I primarily use Data Factory for creating pipelines on cloud in terms of integrating multiple cloud services.

Data Factory's best feature is the ease of setting up pipelines for data and cloud integrations. It also has good integration with other Azure services.

Data Factory could be improved in terms of data transformations by adding more metadata extractions.

I've been using Data Factory for five years.

Data Factory's stability has improved following some initial issues.

Data Factory's scalability is good.

The initial setup was easy as it's a SaaS offering.

Data Factory is affordable.

I would give Data Factory a rating of eight out of ten.

Our primary use case is data loading.

The most valuable features are data transformations.

The speed and performance can be further improved.

This solution should be able to connect with custom APIs.

We have been using this solution for one or two months.

The stability of the Azure Data Factory is very good.

The scalability is good. We have about five users for this solution and they are all developers.

The technical support for this solution is good.

We did not use another solution prior to this one.

The initial setup of the Azure Data Factory was simple. It took us one week to deploy it.

We deployed this solution with our in-house team.

Good

Our licensing fees are approximately 15,000 ($150 USD) per month. There are no additional fees.

We evaluated a solution by Talend before selecting the Azure Data Factory.

My advice for anybody who is implementing this solution is to first get in touch with the Microsoft team to get their support so that you don't spend too much on research.

I would rate this solution a eight out of ten.

We use the solution to move data from on-premises to the cloud.

The tool’s workflow is not user-friendly. It should also improve its orchestration monitoring.

I have been using the product since 2019.

The tool is a stable product.

I would rate the solution a seven out of ten.