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."The solution has a good interface and the integration with GitHub is very useful."
"For me, it was that there are dedicated connectors for different targets or sources, different data sources. For example, there is direct connector to Salesforce, Oracle Service Cloud, etcetera, and that was really helpful."
"The best part of this product is the extraction, transformation, and load."
"This solution will allow the organisation to improve its existing data offerings over time by adding predictive analytics, data sharing via APIs and other enhancements readily."
"What I like best about Azure Data Factory is that it allows you to create pipelines, specifically ETL pipelines. I also like that Azure Data Factory has connectors and solves most of my company's problems."
"The data copy template is a valuable feature."
"The most valuable feature is the ease in which you can create an ETL pipeline."
"It is easy to deploy workflows and schedule jobs."
"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."
"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."
"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."
"We require Azure Data Factory to be able to connect to Google Analytics."
"Data Factory's performance during heavy data processing isn't great."
"There are limitations when processing more than one GD file."
"There's space for improvement in the development process of the data pipelines."
"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."
"Lacks in-built streaming data processing."
"Some known bugs and issues with Azure Data Factory could be rectified."
"Areas for improvement in Azure Data Factory include connectivity and integration. When you use integration runtime, whenever there's a failure, the backup process in Azure Data Factory takes time, so this is another area for improvement."
"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."
"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."
"The reporting features need improvement. It would be very good for users to have a clear understanding of the status of replication."
"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."
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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