My primary use cases for this solution are integration and connecting to the different data stores where we get data and migration activity, deployment, and integrations into using linked services and deployment models.
Data engineer at Target
Reliable and scalable but setup is complex
Pros and Cons
- "Allows more data between on-premises and cloud solutions"
- "Some of the optimization techniques are not scalable."
What is our primary use case?
How has it helped my organization?
This solution has allowed me to quickly get analysis, sales data, supply chain data, and eCommerce data.
What is most valuable?
The most valuable feature of this solution is that it allows more data between on-premises and cloud solutions. It's also useful for orchestration for complex data flows and allows us to do ETL-based transitions heavily. In addition, it allows us to integrate with other third-party systems and compare features and pricing. Other valuable features include database replication, SQL service products, SLA support, data sharing, vendor lock-in, and support for developer tools.
What needs improvement?
Areas for improvement would be the product's performance and its mapping of data flow. In addition, some of the optimization techniques are not scalable, some naming connections are not supported, and automated testing is not supported in all cases. In the next release, I would like to see support so we can enhance based on the next-level pipelines, writing from scratch, flexible scheduling, and pipeline activity.
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Azure Data Factory
February 2025
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For how long have I used the solution?
I've been using this solution for about a year.
What do I think about the stability of the solution?
This solution is very reliable.
What do I think about the scalability of the solution?
This solution is scalable.
How are customer service and support?
I am satisfied with the technical support.
Which solution did I use previously and why did I switch?
I previously worked with Azure SQL database.
How was the initial setup?
The initial setup was complex, but the deployment only took 30 to 40 minutes.
What's my experience with pricing, setup cost, and licensing?
This product is priced at the market standard, which is good given that the product contains all the available assets.
What other advice do I have?
When selecting services, make sure to choose only those you need in order to reduce your costs. I would rate this solution as seven out of ten.
Disclosure: My company has a business relationship with this vendor other than being a customer: Partner
Sr. Technology Architect at a tech services company with 10,001+ employees
Straightforward and scalable but could be more intuitive
Pros and Cons
- "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."
- "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."
What is our primary use case?
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.
What is most valuable?
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.
What needs improvement?
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.
For how long have I used the solution?
I've been using the solution for one year.
What do I think about the stability of the solution?
In the latest version, the v2 version, the solution is pretty stable. It does not give unknown letters or things like that.
What do I think about the scalability of the solution?
The solution allows you to create reusable components, so it can be scaled pretty easily.
How are customer service and technical support?
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.
How was the initial setup?
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.
What's my experience with pricing, setup cost, and licensing?
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.
What other advice do I have?
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.
Disclosure: I am a real user, and this review is based on my own experience and opinions.
Buyer's Guide
Azure Data Factory
February 2025
Learn what your peers think about Azure Data Factory. Get advice and tips from experienced pros sharing their opinions. Updated: February 2025.
832,138 professionals have used our research since 2012.
CEO - Founder / Principal Data Scientist / Principal AI Architect at Kanayma LLC
Provides great consistency that has made implementations less buggy and less complex
Pros and Cons
- "The function of the solution is great."
- "Lacks a decent UI that would give us a view of the kinds of requests that come in."
What is our primary use case?
We use this solution to quickly instantiate certain components in Azure with the aim of having consistent use of certain components and objects. It provides one point of reference rather than having the need to replicate points of references, and then having to keep them in sync.
How has it helped my organization?
It has helped our company by providing consistency. For example, by making sure that the way certain objects and components are defined is consistent throughout every step. If things change at any point, they should be reflected at all points. It's the consistency that makes implementations less buggy and less complex.
What is most valuable?
The function is the central point of reference and the most valuable thing about Data Factory.
What needs improvement?
I'd like to see videos on YouTube or the Microsoft site with more detailed implementations. The solution lacks a decent UI that allows us to see what kinds of requests are for what objects and how the population of objects is being requested and compared. Right now we have to look at logs to get an idea of what types of calls the data factory receives in what sequence, for example. It would be nice to be able to see it graphically because we currently have to interpret the logs and then create a graphical representation to have an idea of what's going on. In general, it could be simplified and made more user-friendly.
For how long have I used the solution?
I've been using this solution for six months.
What do I think about the stability of the solution?
This solution is stable.
What do I think about the scalability of the solution?
There are thousands of users so the solution is scalable.
How are customer service and support?
The customer service is excellent.
How would you rate customer service and support?
Positive
Which solution did I use previously and why did I switch?
I previously used a combination of solutions to achieve the same end. Data Factory simplifies things which is why we switched to it.
How was the initial setup?
The initial setup was complex. The deployment was carried out in-house and we had around 10 people involved in the implementation.
What was our ROI?
In terms of time and effort savings, we have a return on our investment.
What other advice do I have?
It's important to have a good data model before you start using the solution; an idea of the types of data architecture, data objects and components in order to use them. Because of the lack of more user-friendly interfaces, especially for the people debugging the system, I rate this solution eight out of 10.
Which deployment model are you using for this solution?
Public Cloud
Disclosure: I am a real user, and this review is based on my own experience and opinions.
Works with 5,001-10,000 employees
Easy to set up, and reasonably priced, but the user experience could be improved
Pros and Cons
- "Microsoft supported us when we planned to provision Azure Data Factory over a private link. As a result, we received excellent support from Microsoft."
- "User-friendliness and user effectiveness are unquestionably important, and it may be a good option here to improve the user experience. However, I believe that more and more sophisticated monitoring would be beneficial."
What is most valuable?
Essentially, Azure Data Factory is more aligned to ETL, but I wanted to provide a solution for a full data lake solution where I could leverage functionality, whether it is ETL, data ingestion, data warehousing, or data lake.
What needs improvement?
I was planning to switch to Synapse and was just looking into Synapse options.
I wanted to plug things in and then put them into Power BI. Basically, I'm planning to shift some data, leveraging the skills I wanted to use Synapse for performance.
I am not a frequent user, and I am not an Azure Data Factory engineer or data engineer. I work as an enterprise architect. Data Factory, in essence, becomes a component of my solution. I see the fitment and plan on using it. It could be Azure Data Factory or Data Lake, but I'm not sure what enhancements it would require.
User-friendliness and user effectiveness are unquestionably important, and it may be a good option here to improve the user experience. However, I believe that more and more sophisticated monitoring would be beneficial.
For how long have I used the solution?
I work as an enterprise architect, and I have been using Azure Data Factory for more than a year.
I am working with the latest version.
What do I think about the stability of the solution?
Azure Data Factory is a stable solution.
What do I think about the scalability of the solution?
Azure Data Factory is a scalable product.
In my current company, I have a team of five people, but in my previous organization, there were 20.
How are customer service and support?
Technical support is good. We encountered no technical difficulties. Microsoft supported us when we planned to provision Azure Data Factory over a private link. As a result, we received excellent support from Microsoft.
Which solution did I use previously and why did I switch?
Products such as Azure Data Factory and Informatica Enterprise Data Catalog were evaluated. This is something I'm working on. I work as an enterprise architect, so these are the tools that I frequently use.
Previously, I worked with SSIS. We did not change. Because we were building a cloud-based ETF solution Azure Data Factory was an option, but when it came to on-premises solutions, the SQL server integrating the SSIS tool was one option.
How was the initial setup?
The initial setup is easy.
It took three to four weeks to get up to speed and get comfortable using it.
What's my experience with pricing, setup cost, and licensing?
Pricing appears to be reasonable in my opinion.
What other advice do I have?
My only advice is that Azure Data Factory, particularly for data ingestion, is a good choice. But if you want to go further and build an entire data lake solution, I believe Synapse, is preferred. In fact, Microsoft is developing and designing it in such a way that, it's an entirely clubbing of data ingestion, and data lake, for all things. They must make a decision: is the solution dedicated to only doing that type of data ingestion, in which case I believe Data Factory is the best option.
I would have preferred, but I'm not a frequent user there right now. I need to think beyond Data Factory as an open-source project to include machines and everything else. As a result, as previously stated, Data Factory becomes very small at the enterprise architect level. I was inundated with power automation, power ops, power virtualizations, and everything else in Microsoft that I had to think about.
I would rate Azure Data Factory a seven out of ten.
Disclosure: I am a real user, and this review is based on my own experience and opinions.
General Manager Data & Analytics at a tech services company with 1,001-5,000 employees
Great data pipeline and the orchestration functionality with a good user interface
Pros and Cons
- "The initial setup is very quick and easy."
- "Integration of data lineage would be a nice feature in terms of DevOps integration. It would make implementation for a company much easier. I'm not sure if that's already available or not. However, that would be a great feature to add if it isn't already there."
What is our primary use case?
The solution is primarily used for data integration. We are using it for the data pipelines to get data out of the legacy systems and provide it to the Azure SQL Database. We are using the SQL data source providers mainly.
What is most valuable?
The data pipeline and the orchestration functionality are the most valuable aspects of the solution.
The interface is very good. It seeks to be very responsive and intuitive.
The initial setup is very quick and easy.
What needs improvement?
I'm more of a general manager. I don't have any insights in terms of missing features or items of that nature.
Integration of data lineage would be a nice feature in terms of DevOps integration. It would make implementation for a company much easier. I'm not sure if that's already available or not. However, that would be a great feature to add if it isn't already there.
For how long have I used the solution?
We've used the solution for the last 12 months or so.
What do I think about the stability of the solution?
From what I have witnessed, the solution is quite stable. It doesn't crash or freeze. There are no bugs or glitches. It's reliable.
What do I think about the scalability of the solution?
We work with medium to enterprise-level organizations. Customers have anywhere from 300 employees up to 160,000 employees.
How are customer service and technical support?
Microsoft offers a great community. There's a lot of support available. We're quite satisfied with the level of assistance on offer.
How was the initial setup?
Since the solution is a service, it's basically just a click and run setup. It's very simple. There's very little implementation necessary. A company should be able to easily arrange it. The deployment doesn't take very long at all.
What about the implementation team?
We do provide the implementation for our clients. We're able to provide templates as well. We have predefined implementation space in Data Factory and provide it to the customer.
Which other solutions did I evaluate?
While clients might individually evaluate other options, however, we're not aware of that information. I can't say what other solution clients might consider before ultimately choosing Microsoft. I would say that it is likely Talend and maybe SQL Server Integration Services.
What other advice do I have?
We are like an integrator. We are a data warehouse NPI consulting company and we use Data Factory to pull data from different legacy systems and do all these transformations that are necessary in order to provide analytical models.
In our normal scenario is that we are providing Azure SQL Databases together with Azure Data Factory and Power BI. 80% of our customers have recognized such a scenario.
On a scale from one to ten, I'd rate the solution at an eight. We've been largely happy with the capabilities of the product.
Disclosure: My company has a business relationship with this vendor other than being a customer: Implementator
Chief Analytics Officer at Idiro Analytics
I like that we can set up the security protocols for IP addresses
Pros and Cons
- "It's cloud-based, allowing multiple users to easily access the solution from the office or remote locations. I like that we can set up the security protocols for IP addresses, like allow lists. It's a pretty user-friendly product as well. The interface and build environment where you create pipelines are easy to use. It's straightforward to manage the digital transformation pipelines we build."
- "Data Factory has so many features that it can be a little difficult or confusing to find some settings and configurations. I'm sure there's a way to make it a little easier to navigate."
What is our primary use case?
We use Data Factory for automating ETL processes, data management, digital transformation, and scheduled automated processes. My team has about 11 people, and at least five use Data Factory. It's mostly data engineers and analysts.
Each data analyst and engineer manages a few projects for clients. Typically, it's one person per client, but we might have two or three people managing and building out pipelines for a larger project.
What is most valuable?
It's cloud-based, allowing multiple users to easily access the solution from the office or remote locations. I like that we can set up the security protocols for IP addresses, like allow lists. It's a pretty user-friendly product as well. The interface and build environment where you create pipelines are easy to use. It's straightforward to manage the digital transformation pipelines we build.
What needs improvement?
Data Factory has so many features that it can be a little difficult or confusing to find some settings and configurations. I'm sure there's a way to make it a little easier to navigate.
In the main ADF web portal could, there's a section for monitoring jobs that are currently running so you can see if recent jobs have failed. There's an app for working with Azure in general where you can look at some segs in your account. It would be nice if Azure had an app that lets you access the monitoring layer of Data Factory from your phone or a tablet, so you could do a quick check-in on the status of certain jobs. That could be useful.
For how long have I used the solution?
We've been using Azure Data Factory for about three years.
What do I think about the stability of the solution?
I've been happy with it overall. I don't think we've had any major issues. We've been able to do what we needed, whether connecting to different data sources or setting up different types of transformations and processes.
What do I think about the scalability of the solution?
It's a cloud solution, so it's inherently scalable. I don't know If we have to raise the limits on resources like clusters and processing power or if it will just automatically scale up. I can't remember offhand.
Which solution did I use previously and why did I switch?
We managed the same actions with a combination of tools. We used SFTP servers to move data from one place to another. We used scripts for loading and some other stored procedures or processes for data transformation within a database. It took two or three pieces of technology or systems to manage the same types of operation. Data Factory lets us consolidate those steps into a single pipeline.
How was the initial setup?
Setting up Azure Data Factory is pretty straightforward. We had an Azure account already, and Data Factory was just something we could add as an extra service. We had to create instances and pipelines, and it took us about two weeks to get our first pipelines scheduled and running.
What about the implementation team?
We do everything in-house.
What was our ROI?
We see a return on Data Factory if we compare the time and effort that would be necessary to perform the equivalent processes manually.
What's my experience with pricing, setup cost, and licensing?
I'm not too familiar with the cost, but I believe we're reasonably happy with what we're paying. My understanding is that the cost of Data Factory is tied to consumption. It depends on the amount of data or the number of pipelines running, and the cost varies from month to month depending on the usage.
You'll obviously pay more if you're scheduling heavy digital transformation processes to run every hour, but I don't think there are any other hidden costs or anything extra. When you set up a new account, you have a trial period that enables you to create a test pipeline or process that's typical of your use case and then do a benchmark test to see if Data Factory can achieve the efficiency you need. You'll also get some idea of how much the process will cost to run. From there, it's straightforward to do a cost evaluation or comparison to see if it's the right fit for your company.
Which other solutions did I evaluate?
We were looking for a single solution, and Data Factory was the first one that interested us. I don't think we looked at many others. We were pretty set on Azure, and Data Factory seemed to fit our needs, so we didn't make a full comparison with the alternatives.
What other advice do I have?
I rate Azure Data Factory nine out of 10. It isn't perfect, but it's solid. Data Factory has improved how we deal with various aspects of Azure. It has always met our needs in terms of the transformations and jobs we want to create and schedule.
Which deployment model are you using for this solution?
Public Cloud
Disclosure: My company has a business relationship with this vendor other than being a customer: Partner
ETL Developer at Det Norske Veritas
Stable, scalable solution that's great for copying data
Pros and Cons
- "Data Factory's most valuable feature is Copy Activity."
- "Data Factory's cost is too high."
What is our primary use case?
I mainly use Data Factory to load data for ETL processes or to Azure Storage and for testing purposes in our business unit.
What is most valuable?
Data Factory's most valuable feature is Copy Activity.
For how long have I used the solution?
I've been using Data Factory for around two years.
What do I think about the stability of the solution?
Data Factory is stable.
What do I think about the scalability of the solution?
We've had no problems with Data Factory's scalability.
How are customer service and support?
Microsoft's technical support is responsive and quick to help.
What about the implementation team?
We used consultants to implement Data Factory.
What's my experience with pricing, setup cost, and licensing?
Data Factory's cost is too high.
What other advice do I have?
I would advise anybody thinking of implementing Data Factory to calculate their costs at the initial stage in order to have some knowledge about future costs for the whole project. I would rate Data Factory as eight out of ten.
Which deployment model are you using for this solution?
On-premises
Disclosure: I am a real user, and this review is based on my own experience and opinions.
Independent consultant at a hospitality company with 1-10 employees
Has a user-friendly interface and robust data-monitoring capabilities
Pros and Cons
- "The platform excels in data transformation with its user-friendly interface and robust monitoring capabilities, making ETL processes seamless."
- "The product integration with advanced coding options could cater to users needing more customization."
What is our primary use case?
The platform simplifies data access and visualization with minimal coding, catering to various data management needs across different client projects.
How has it helped my organization?
The product centralizes data workflows, enhancing data integration efficiency and visualization for comprehensive analysis.
What is most valuable?
The platform excels in data transformation with its user-friendly interface and robust monitoring capabilities, making ETL processes seamless.
What needs improvement?
The product integration with advanced coding options could cater to users needing more customization.
For how long have I used the solution?
I've been using Azure Data Factory for almost a year now.
What do I think about the stability of the solution?
The product is stable.
What do I think about the scalability of the solution?
The product is scalable.
How was the initial setup?
The initial setup process is straightforward.
What's my experience with pricing, setup cost, and licensing?
Azure products generally offer competitive pricing, suitable for diverse budget considerations.
What other advice do I have?
Data Factory integrates seamlessly within the Azure ecosystem, offering robust data management capabilities across large-scale projects.
I rate it a nine out of ten.
Disclosure: I am a real user, and this review is based on my own experience and opinions.
Last updated: Jul 30, 2024
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