We performed a comparison between Azure Data Factory and Qlik Replicate based on real PeerSpot user reviews.
Find out in this report how the two Data Integration solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
"I like its integration with SQL pools, its ability to work with Databricks, its pipelines, and the serverless architecture are the most effective features."
"The initial setup is very quick and easy."
"The most valuable features of Azure Data Factory are the flexibility, ability to move data at scale, and the integrations with different Azure components."
"The data copy template is a valuable feature."
"I like the basic features like the data-based pipelines."
"It makes it easy to collect data from different sources."
"The most valuable aspect is the copy capability."
"ADF is another ETL tool similar to Informatica that can transform data or copy it from on-prem to the cloud or vice versa. Once we have the data, we can apply various transformations to it and schedule our pipeline according to our business needs. ADF integrates with Databricks. We can call our Databricks notebooks and schedule them via ADF."
"It's very user-friendly when it comes to settings and configuration. It also offers very detailed logging about warnings and errors."
"The most useful functions of Qlik Replicate are the data manipulation to transformations."
"The CDC and the flexibility to use QVD as a source are the most valuable features of Qlik Replicate."
"We use Qlik Replicate to change data capture of databases in production environments."
"The main valuable feature is its real-time change data capture (CDC) capabilities, which process data with minimal latency. There is not much delay. It also performs well with batch-wise data applications."
"A valuable feature of Qlik Replicate is that you do not need ETL. It's easy to use—you choose two systems and it automatically replicates them. Even if there is no CDC available, if you insert it and update it, and there is nothing to find out, then you can use Qlik Replicate. It's a good product."
"From a technical perspective, this is an excellent product."
"It enables us to transform data at the latest stage rather than in ETL loads, so it's more ELT which is one of the advantages. It is also in near real-time, which brings significant advantage for our embedded analytics approach."
"They require more detailed error reporting, data normalization tools, easier connectivity to other services, more data services, and greater compatibility with other commonly used schemas."
"We require Azure Data Factory to be able to connect to Google Analytics."
"Lacks a decent UI that would give us a view of the kinds of requests that come in."
"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."
"There is no built-in pipeline exit activity when encountering an error."
"Data Factory would be improved if it were a little more configuration-oriented and not so code-oriented and if it had more automated features."
"The solution needs to integrate more with other providers and should have a closer integration with Oracle BI."
"Currently, our company requires a monitoring tool, and that isn't available in Azure Data Factory."
"Support-wise, this solution is in need of improvement."
"In the next release, I would like to see closer integration with data catalyst."
"In various scenarios, an important consideration is when we encounter issues and Qlik Replicate suggests reloading a specific table. If we face any problems or encounter errors with that table, it becomes necessary to make a change in Qlik Replicate. Performing a full reload every time is not feasible or practical. Instead, we should identify the specific issues and address them without repeating the entire reloading process. Based on this approach, we can investigate and resolve the problem by performing targeted loads from the source itself. This change aligns with my perspective and is something I would like to implement."
"It's not possible to replicate the QVC files in data analytics."
"Support for this product is not great. It needs to be improved."
"The UI and data version control can be improved."
"It would be better if the solution’s pricing were more obvious."
"This product could be improved by providing more insight regarding errors. One of our customers that uses Qlik Replicate has had an issue. We tried to debug it, but we could not trace the error message. The infrastructure site should give us more insight about errors. Qlik Replicate is not a business solution, it's an IT solution. The reporting tools and bug site should be improved."
Azure Data Factory is ranked 1st in Data Integration with 81 reviews while Qlik Replicate is ranked 16th in Data Integration with 13 reviews. Azure Data Factory is rated 8.0, while Qlik Replicate is rated 8.2. The top reviewer of Azure Data Factory writes "The data factory agent is quite good but pricing needs to be more transparent". On the other hand, the top reviewer of Qlik Replicate writes " Performs well with batch-wise data applications but some features can also be overly dependent on each other". Azure Data Factory is most compared with Informatica PowerCenter, Informatica Cloud Data Integration, Alteryx Designer and Snowflake, whereas Qlik Replicate is most compared with Oracle GoldenGate, AWS Database Migration Service, Qlik Compose, Fivetran and SSIS. See our Azure Data Factory vs. Qlik Replicate report.
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