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.
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Qlik Replicate
Score 10.0 out of 10
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Qlik Replicate enables organizations to accelerate data real-time replication, ingestion and streaming via change data capture, across a wide range of heterogeneous databases, data warehouses and data lake platforms.
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Pricing
Azure Data Factory
Qlik Replicate
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Azure Data Factory
Qlik Replicate
Free Trial
No
Yes
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
Yes
Entry-level Setup Fee
No setup fee
Required
Additional Details
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More Pricing Information
Community Pulse
Azure Data Factory
Qlik Replicate
Considered Both Products
Azure Data Factory
No answer on this topic
Qlik Replicate
Verified User
Employee
Chose Qlik Replicate
Qlik Replicate is fast and easy. ADF can do a wider variety of things
Best scenario is for ETL process. The flexibility and connectivity is outstanding. For our environment, SAP data connectivity with Azure Data Factory offers very limited features compared to SAP Data Sphere. Due to the limited modelling capacity of the tool, we use Databricks for data modelling and cleaning. Usage of multiple tools could have been avoided if adf has modelling capabilities.
Qlik Replicate works very well with relational data platforms, both on premise and in the cloud, for example Oracle, SQL Server, PostgreSQL, MySQL and others, it also works very well with DB2. If the data source is MongoDB, it is more complicated and currently there is no possibility of sending data to MongoDB.
Replicate is extremely stable and does not generate a lot of alerts/failures/issues that take up time to troubleshoot.
It is very easy to add new source tables to a Replicate task so that we're always in sync with new data available from the CRM.
It's nice that Qlik Replicate also allows you to create a job to stop and then restart your tasks during maintenance windows that occur on both the source and target systems.
Granularity of Errors: Sometimes, Azure Data Factory provides error messages that are too generic or vague for us, making it challenging to pinpoint the exact cause of a pipeline failure. Enhanced error messages with more actionable details would greatly assist us as users in debugging their pipelines.
Pipeline Design UI: In my experience, the visual interface for designing pipelines, especially when dealing with complex workflows or numerous activities, can become cluttered. I think a more intuitive and scalable design interface would improve usability. In my opinion, features like zoom, better alignment tools, or grouping capabilities could make managing intricate designs more manageable.
Native Support: While Azure Data Factory does support incremental data loads, in my experience, the setup can be somewhat manual and complex. I think native and more straightforward support for Change Data Capture, especially from popular databases, would simplify the process of capturing and processing only the changed data, making regular data updates more efficient
The base Replicate web GUI is lacking. If you have dozens or more tasks, it's hard to get a sense of how they're performing. Enterprise Manager solves all of these problems but is a separate install.
The support portal is extremely difficult to navigate. It's hard to track down exactly what you're looking for.
It would be helpful to have better documentation and example queries for the tables in the Enterprise Manager analytics database.
Destination databases that don't support common DDL commands behave unpredictably. And the replication of schema changes isn't consistent.
The availability of the replicated data in disparate environments has is now crucial. Replacing a product like Qlik Replicate would require significant time, investments, and work. In addition, Qlik Replicate is reasonably reliable with few failures.
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.
We now have greater business flexibility and scalability, and our big data integration projects have a quick rate of growth, which has been profitable for us. Independent of the sources involved, maintaining data consistency between sources is easy. One of my favorite features is the way it lets owners of the source system start and stop processes from updating their system windows.
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
The issue I've had is that Qlik does an awful job of keeping their customers informed when new versions of the software are available. We found that we were using a version that was no longer supported and could never get help. When it came time to get us upgraded so that we were on a current version, no one knew how to help get us to where we needed to be. We had to purchased professional services time and even then I was basically on my own to get everything built out and set up. Qlik needs to be more proactive with communicating about new releases and how to get your version upgraded in the most secure, safe way possible.
Follow the directions from the Qlik documentation. They are pretty straight forward and easy enough to follow. If you follow these, then you are not likely to have issues on implementation.
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 programming languages like Python or automation tools like ansible. Numerous options for connectivity be it a database or storage account helps us move data transfer to the cloud or on-premise systems.
Great tool for data replication solution for Oracle/SQLServers/etc. Real easy to get it set up and start realizing business value. Getting the PoC accomplished in a short window. Product costing and easy to start small and scale as needed. It helped cover most of our ask compared to other solutions.
Prior to using Qlik Replicate, we used an ETL solution to copy data from the Oracle ERP system to the Microsoft SQL Server BI system at a 15-minute interval. It was very tedious to maintain. Qlik Replicate is much easier to use and we replicate data near real-time now.
