We performed a comparison between Azure Data Factory and Quest SharePlex 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."One of the most valuable features of Azure Data Factory is the drag-and-drop interface. This helps with workflow management because we can just drag any tables or data sources we need. Because of how easy it is to drag and drop, we can deliver things very quickly. It's more customizable through visual effect."
"I am one hundred percent happy with the stability."
"It has built-in connectors for more than 100 sources and onboarding data from many different sources to the cloud environment."
"We haven't had any issues connecting it to other products."
"It is a complete ETL Solution."
"I like how you can create your own pipeline in your space and reuse those creations. You can collaborate with other people who want to use your code."
"Allows more data between on-premises and cloud solutions"
"The most valuable features of the solution are its ease of use and the readily available adapters for connecting with various sources."
"The core features of the solution we like are the reliability of the data transfer and the accuracy of data read and write. The stability of the solution is also excellent."
"Because of the volume of the transactions, we heavily use a feature that allows SharePlex to replicate thousands of transactions. It's called PEP, Post Enhancement Performance, and that has helped us scale tremendously."
"The core replication and its performance. Performance is crucial, and SharePlex is by far the fastest. The way it handles replication to multiple targets along with basic filtering, as well as from multiple sources to a single target, is very efficient."
"I like SharePlex's Compare and Repair tool."
"There are some capabilities within SharePlex where you can see how the data is migrating and if it still maintains good data integrity. For example, if there are some tables that get out of sync, there are ways to find them and fix the problem on the spot. Since these are very common issues, we can easily fix these types of problems using utilities, like compare and repair. So, if you find something is out of sync, then you can just repair that table. It basically syncs that table from source to target to see if there are any differences. It will then replicate those differences to the target."
"The pricing scheme is very complex and difficult to understand."
"My only problem is the seamless connectivity with various other databases, for example, SAP."
"There's space for improvement in the development process of the data pipelines."
"The performance could be better. It would be better if Azure Data Factory could handle a higher load. I have heard that it can get overloaded, and it can't handle it."
"Data Factory could be improved by eliminating the need for a physical data area. We have to extract data using Data Factory, then create a staging database for it with Azure SQL, which is very, very expensive. Another improvement would be lowering the licensing cost."
"It would be better if it had machine learning capabilities."
"The solution needs to integrate more with other providers and should have a closer integration with Oracle BI."
"DataStage is easier to learn than Data Factory because it's more visual. Data Factory has some drag-and-drop options, but it's not as intuitive as DataStage. It would be better if they added more drag-and-drop features. You can start using DataStage without knowing the code. You don't need to learn how the code works before using the solution."
"I don't know how easy it would be to change the architecture in an already implemented replication. For example, if we have a certain way of architecting for a particular database migration and want to change that during a period of time, is that an easy or difficult change? There was a need for us to change the architecture in-between the migration, but we didn't do it. We thought, "This is possibly complicated. Let's not change it in the middle because we were approaching our cutover date." That was one thing that we should have checked with support about for training."
"The reporting features need improvement. It would be very good for users to have a clear understanding of the status of replication."
"I would like more ability to automate installation and configuration in line with some of the DevOps processes that are more mature in the market. That would be a considerable improvement."
"I would like the solution to have some kind of machine learning and AI capabilities. Often, if we want to improve the performance of posting, we have to bump up a parameter. That means we need to stop the process, come up with a figure that we want to bump the parameter up to, and then start SharePlex. Machine learning and AI capabilities for these kinds of improvement would tremendously help boost productivity for us."
"For its function in relation to replication (i.e. filtering), I'd give it a six or seven out of 10. GoldenGate has much more functionality by comparison."
Azure Data Factory is ranked 1st in Data Integration with 81 reviews while Quest SharePlex is ranked 24th in Data Integration with 5 reviews. Azure Data Factory is rated 8.0, while Quest SharePlex is rated 9.0. 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 Quest SharePlex writes "It reduces the downtime and migration time exponentially". Azure Data Factory is most compared with Informatica PowerCenter, Informatica Cloud Data Integration, Alteryx Designer, Snowflake and Microsoft Azure Synapse Analytics, whereas Quest SharePlex is most compared with Oracle GoldenGate, AWS Database Migration Service, Qlik Replicate, Oracle Enterprise Manager and Fivetran. See our Azure Data Factory vs. Quest SharePlex report.
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