Azure Data Factory Reviews

We use this solution for data integration. We use it to feed operational data into a data warehouse. We also use it for creating connections between applications.

Within our organization, there are a few thousand users of Azure Data Factory.

We believe that the number of customers and usage of this product will extend over the next few years. For this reason, we invest a lot of resources in building skills, and we make sure to hire consultants who know their way around Data Factory.

The flexibility that Azure Data Factory offers is great.

The number of standard adaptors could be extended further. What we find is that if we develop data integration solutions with Data Factory, there's still quite a bit of coding involved, whereas we'd like to move in a direction with less coding and more select-and-click.

I have been using Azure Data Factory for one year.

We don't have any complaints regarding scalability or stability.

I think Microsofts' technical support does a pretty good job. There is a lot of information available on the internet to find out how to use their products. There's also quite an active community. If you really can't find a solution, you can always call Microsoft. Our organization is partnered with Microsoft, so we usually get answers directly from them.

We used SSIS. We're still using SSIS. SSIS is an old product. The development of SSIS has more or less stopped and the development is now focused on cloud services — it's the future. Azure Data Factory Is great because it's a cloud service; you do not have to take care of the installation and configuration yourself. The cost buildup is also quite different. I am not sure that's a huge financial advantage yet, but we do believe that it will be in the future.

The initial setup was straightforward.

We didn't have to deploy Azure Data Factory. It's available as an Azure service, so Microsoft takes care of that.

It's a pay-per-use model. So if you run it, it's hardly licensing. The entire cost of Azure is per-use. The price you pay is determined by how much you use it.

I would definitely recommend Azure Data Factory. On a scale from one to ten, I would give this solution a rating of eight. 

If there were a larger amount of automated features, I would give them a higher rating. As I mentioned earlier, if we are working on complex applications, then there is a lot of coding involved. What we hope is that over time, there'll be less coding and more "off the shelf" functionality.

The primary use case of this solution is for data integration.

It has built-in connectors for more than 100 sources and onboarding data from many different sources to the cloud environment.

It has everything we needed.

Being able to post your feedback and queries is a very good feature that is offered by Azure Data Factory.

Understanding the pricing model for Data Factory is quite complex. It needs to be simplified, and easier to understand.

We have experienced some issues with the integration. This is an area that needs improvement.

I have been using this solution for almost two years.

So far it's been stable. We have not experienced any issues.

I haven't put much thought into scalability.

I have contacted technical support.

If there are any queries, they have the provision to post them in the Data Factory GUI and we can contact the team directly. This is a very nice feature.

Any feedback or improvements that we post is acknowledged and taken care of.

The initial setup was straightforward. It was not complex.

Pricing is quite complex.

I have had feedback from many people and many of my team members, and they say that it is difficult to understand. 

Understanding the pricing of Data Factory is quite complex. 

It is not presented in a straightforward way.

I would definitely recommend this solution to anyone who is interested in using it.

I would rate Azure Data Factory an eight out of ten.

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.

I primarily use the solution for my small and medium-sized clients.

So far, I'm quite happy with the solution overall. It's got a lot of tools that I use in my work, and these are items I'm already recommending to my clients. I'm quite happy with it.

I'm not sure if I have any complaints about the solution at the moment. There are a few bits and pieces that we would like to see improved. These include improvements related to the solution's ease of use and some quality flash upgrades. However, these are minor complaints. 

If the user interface was more user friendly and there was better error feedback, it would be helpful.

I've been working with the solution for three to four years now.

On the tool itself, we've never experienced any bugs or glitches. There haven't been crashes. Stability has been good.

I haven't had the ability to scale any of my projects personally. I also wouldn't need to scale too high if I did. I'm not sure if I can speak to aspects of scalability as I've never dealt with it.

I've contacted Microsoft technical support in the past. I have to say that I've had a good experience with them. I've been quite satisfied with their level of service.

The initial setup was very straightforward. I wouldn't describe it as complex.

Deployment is fast. It only takes about half an hour at most.

I don't have any information about the pricing. I don't deal with that aspect of the solution.

I typically work with small to medium-sized companies. I'm a consultant, so I give different advice based on what my clients need and what they want to do. However, I would recommend this product. 

I'd rate the solution eight out of ten. All of the issues I have with the solution are very minor, however, it means the solution isn't exactly perfect just yet.

We are a tech services company and this is one of the tools that we use when implementing solutions for our clients. I am currently managing a team that is working with the Azure Data Factory.

Our clients that use this solution are migrating their data from on-premises to the cloud.

One of our clients is building an integrated data warehouse for all of their data, using this solution. It is used to extract all of the data from different servers and store it into one place.

Our clients find that this solution has a very good performance. They like the speed.

It is easy to deploy workflows and schedule jobs. You can just click on the desktop and it works.

The setup and configuration process could be simplified.

We have been using Azure Data Factory for the past six months.

This is a stable product and we're expecting more updates from Microsoft. We have not used more than one terabyte of data so that remains untested, but for one terabyte it works fine.

Development is only done on an occasional basis, but the solution is used every day. If it is streaming data then the process is continuous, otherwise, it is initiated by the user on demand.

This solution is 100% scalable.

We have two clients working with this solution.

It is another team who is responsible for contacting technical support.

We have used other ETL solutions in the past, and Azure Data Factory is the best one. Compared to SSIS, for example, ADF is easier to use and the performance is better.

Our clients are migrating from on-premises SSIS solutions to the cloud because they want to take advantage of the latest technologies.

The installation is very simple and it doesn't take much time. For us, the deployment took about two days, which does not seem unreasonable for something that is on the cloud. Most of the time is spent waiting for credentials.

Depending on the sources of the data, four people are required for deployment and maintenance. If the sources are SQL databases then it is straightforward and four people can cope with it. If the data is more difficult then we may need more people.

The deployment is done in-house with a technical person with knowledge of the Azure cloud.

This is a cost-effective solution.

We have another team that is moving to AWS, but for now, we will continue working with Azure Data Factory. Once they have explored the AWS solution fully, we will compare the two.

Within the next six months, we are planning to enter into the machine learning part of this solution. This is a product that I can recommend.

I would rate this solution an eight out of ten.

The features that I've found most valuable, in order: That it is a complete ETL Solution, the second one is interface, the third one workflow, and the fourth one ease of use.

The only thing that we're struggling with is increasing the competency of my team. So we think that the Microsoft documentation is too complicated.

I would like to see it more connected. I know they're working on the Snowflake data warehouse connector, but more connectors would be helpful.

I've been using Azure Data Factory for a few months.

It is stable.

Azure Data Factory is a scalable solution.

In terms of support, we haven't used the direct support but the community support is very good.

We previously used the Oracle Warehouse Builder. The reasons we stopped using it were that Warehouse Builder is at the end of its life-cycle and its slow performance.

The initial setup is complex.

We first implemented it ourselves but we're using a partner now. We thought we could do it ourselves but we needed specialty help.

I would highly recommend Azure Data Factory as it has proof of concept.

We have nine people using Azure Data Factory.

On a scale of one to ten, I give it an eight.

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.  

There was a need to bring a lot of CRM and marketing data for some PNL analysis. We are connecting to the Salesforce cloud. In it, there's a specific solution in Salesforce Core CRM for the pharmaceutical industry. We are using the solution to connect to that and we are bringing in the various dimensions and transactions from that data source.

Data Factory itself is great. It's pretty straightforward. You can easily add sources, join and lookup information, etc. The ease of use is pretty good. 

They have a lot of other components like a newer monitor, which helps track and generate alerts for any failed jobs and things of that nature, which is helpful.

At this point in time, they should work on somehow integrating the big data capabilities within it. I have not explored it, but it would be good if somehow we could call a Spark job or something to do with the Spark SQL within ADS so that we wouldn't need a Spark tested outside.

On the UI side, they could make it a little more intuitive in terms of how to add the radius components. Somebody who has been working with tools like Informatica or DataStage gets very used to how the UI looks and feels. 

In ADS, adding a new table or joining a new table and overriding that with an override SQL that I could customize would be helpful.

Being able to debug from the design mode itself would be helpful.

I've been using the solution for one year.

In the latest version, the v2 version, the solution is pretty stable. It does not give unknown letters or things like that.

The solution allows you to create reusable components, so it can be scaled pretty easily.

Being an IT services company, we have a gold or a platinum partnership with Microsoft. For us, getting the technical support we need is not a big issue. Their community is also pretty active in responding to any issues. It's quite good. We've been satisfied with the level of support that is offered.

We were not actually involved in the initial setup. That was all with the client, so I won't be able to comment on it.

In terms of licensing costs, we pay somewhere around S14,000 USD per month. There are some additional costs. For example, we would have to subscribe to some additional computing and for elasticity, but they are minimal. 

For disaster recovery and readability setups, we did that on Data Lake.

We use the public cloud deployment model.

I'd warn others to ensure that the design should be frozen before you start building because overriding each other's code and managing code takes effort. To avoid or to reduce that effort, ensure that the design is frozen. You can build some configurable code rather than hard-coding everything into the jobs. That's the biggest recommendation.

I'd rate the solution seven out of ten. It's a pretty good solution, but over the past year, I've been limited on the number of cases I have on it. If it had a better user interface and was more intuitive I would have rated it higher.