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."Allows more data between on-premises and cloud solutions"
"Data Factory's best features include its data source connections, GUI for building data pipelines, and target loading within Azure."
"I like that it's a monolithic data platform. This is why we propose these solutions."
"On the tool itself, we've never experienced any bugs or glitches. There haven't been crashes. Stability has been good."
"It is a complete ETL Solution."
"This solution has provided us with an easier, and more efficient way to carry out data migration tasks."
"The most valuable feature of this solution would be ease of use."
"It makes it easy to collect data from different sources."
"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 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."
"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."
"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."
"One area for improvement is documentation. At present, there isn't enough documentation on how to use Azure Data Factory in certain conditions. It would be good to have documentation on the various use cases."
"There is always room to improve. There should be good examples of use that, of course, customers aren't always willing to share. It is Catch-22. It would help the user base if everybody had really good examples of deployments that worked, but when you ask people to put out their good deployments, which also includes me, you usually got, "No, I'm not going to do that." They don't have enough good examples. Microsoft probably just needs to pay one of their partners to build 20 or 30 examples of functional Data Factories and then share them as a user base."
"We have experienced some issues with the integration. This is an area that needs improvement."
"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."
"Currently, our company requires a monitoring tool, and that isn't available in Azure Data Factory."
"It's a good idea to take a Microsoft course. Because they are really helpful when you start from your journey with Data Factory."
"It does not appear to be as rich as other ETL tools. It has very limited capabilities."
"Azure Data Factory should be cheaper to move data to a data center abroad for calamities in case of disasters."
"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 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."
"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."
"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."
Azure Data Factory is ranked 1st in Data Integration with 79 reviews while Quest SharePlex is ranked 22nd 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, Alteryx Designer, Informatica Cloud Data Integration, 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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