Azure Data Factory vs Quest SharePlex comparison

Microsoft and Quest Software are both solutions in the Data Integration category. Microsoft is ranked #1 with an average rating of 8.1, while Quest Software is ranked #48. Microsoft holds a 11.0% mindshare in DI, compared to Quest Software’s 0.8% mindshare. Additionally, 92% of Microsoft users are willing to recommend the solution, compared to 100% of Quest Software users who would recommend it.

Azure Data Factory

Read 86 Azure Data Factory reviews

21,615 Views
17,232 Comparison Views

92% willing to recommend

Quest SharePlex

Read 5 Quest SharePlex reviews

1,862 Views
1,168 Comparison Views

100% willing to recommend

Azure Data Factory

Quest SharePlex

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 19, 2024

Quest SharePlex and Azure Data Factory cater to data management, with SharePlex excelling in database replication and Azure Data Factory standing out in data integration, giving Azure a slight advantage for users requiring comprehensive integration features.

Features: Quest SharePlex offers robust database replication, ideal for scenarios needing constant uptime, efficient data recovery, and reliable data transfer. Azure Data Factory provides extensive data integration features with cloud and on-premises systems, scalable performance, advanced ETL capabilities, and connectivity with diverse data sources.

Room for Improvement: Quest SharePlex could enhance its data integration abilities, user interface, and expand its support for cloud technologies. Azure Data Factory would benefit from simpler initial setup, more intuitive ETL processes, and improved real-time data processing features.

Ease of Deployment and Customer Service: Quest SharePlex is known for seamless deployment with minimal system impact, making it favorable for hybrid scenarios, along with strong technical support. Azure Data Factory integrates effortlessly within Microsoft's ecosystem, though it may require more initial setup; however, Microsoft provides extensive customer service with multiple support options.

Pricing and ROI: Quest SharePlex involves initial licensing costs with predictable expenses, offering a clear ROI for reliable data replication. Azure Data Factory operates on a pay-as-you-go model, which might result in lower upfront costs but could lead to variable expenses, providing favorable ROI for projects leveraging Azure's services, particularly in integration-heavy use cases.

To learn more, read our detailed Azure Data Factory vs. Quest SharePlex Report (Updated: December 2024).

Buyer's Guide

Azure Data Factory vs. Quest SharePlex

December 2024

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Categories and Ranking

Azure Data Factory

Ranking in Data Integration

1st

Average Rating

8.0

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

Cloud Data Warehouse (3rd)

Quest SharePlex

Ranking in Data Integration

48th

Average Rating

9.0

Reviews Sentiment

7.2

Number of Reviews

Ranking in other categories

Database Development and Management (24th)

Mindshare comparison

As of December 2024, in the Data Integration category, the mindshare of Azure Data Factory is 11.0%, down from 13.3% compared to the previous year. The mindshare of Quest SharePlex is 0.8%, down from 1.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration

Featured Reviews

Thulani David Mngadi

Data architect at Old Mutual

Data flow feature is valuable for data transformation tasks

The workflow automation features in GitLab, particularly its low code/no code approach, are highly beneficial for accelerating development speed. This feature allows for quick creation of pipelines and offers customization options for integration needs, making it versatile for various use cases. GitLab supports a wide range of connectors, catering to a majority of integration needs. Azure Data Factory's virtual enterprise and monitoring capabilities, the visual interface of GitLab makes it user-friendly and easy to teach, facilitating adoption within teams. While the monitoring capabilities are sufficient out of the box, they may not be as comprehensive as dedicated enterprise monitoring tools. GitLab's monitoring features are manageable for production use, with the option to integrate log analytics or create custom dashboards if needed. The data flow feature in Azure Data Factory within GitLab is valuable for data transformation tasks, especially for those who may not have expertise in writing complex code. It simplifies the process of data manipulation and is particularly useful for individuals unfamiliar with Spark coding. While there could be improvements for more flexibility, overall, the data flow feature effectively accomplishes its purpose within GitLab's ecosystem.

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Kristopher Wells

Oracle DBA at Broadridge Financial Solutions, Inc.

It reduces the downtime and migration time exponentially

I would rate SharePlex's high availability, and disaster recovery features highly. It works as advertised in terms of rapid fill-over and switch-over opportunities. It reduces the migration time for a multi-terabyte database to an hour or less because it performs real-time replication. SharePlex reduces downtime and migration time exponentially. Something that could take 12 to 24 hours is cut down to one to two hours. By the time you start to migrate, the only remaining replication is a slight difference in data from the point when SharePlex has shut down, and the application has to also switch over to the new database. It allowed the company to replicate data more transparently. Some of the business executives probably don't even know it's there. It works 100 percent of the time, with little downtime or problems. It provides what is needed. There's little concern about whether or not it functions. It's allowed the company to achieve its objectives with its clients, reducing and minimizing downtime for substantial migrations and upgrades. It can reduce hardware and storage costs, but my company doesn't utilize it with high-availability architecture.

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Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros

"The overall performance is quite good."

"The most valuable feature is the copy activity."

"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 scalability of the product is impressive."

"I like the basic features like the data-based pipelines."

"One advantage of Azure Data Factory is that it's fast, unlike SSIS and other on-premise tools. It's also very convenient because it has multiple connectors. The availability of native connectors allows you to connect to several resources to analyze data streams."

"The most valuable feature of Azure Data Factory is that it has a good combination of flexibility, fine-tuning, automation, and good monitoring."

"From what we have seen so far, the solution seems very stable."

More Azure Data Factory pros

"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."

"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 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."

Cons

"The setup and configuration process could be simplified."

"The initial setup is not very straightforward."

"You cannot use a custom data delimiter, which means that you have problems receiving data in certain formats."

"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 deployment should be easier."

"The need to work more on developing out-of-the-box connectors for other products like Oracle, AWS, and others."

"Some known bugs and issues with Azure Data Factory could be rectified."

"The solution can be improved by decreasing the warmup time which currently can take up to five minutes."

More Azure Data Factory cons

"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."

"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."

"The reporting features need improvement. It would be very good for users to have a clear understanding of the status of replication."

Pricing and Cost Advice

"Pricing is comparable, it's somewhere in the middle."

"The price you pay is determined by how much you use it."

"I am aware of the pricing of Azure Data Factory, but I prefer not to disclose specific details."

"I rate the product price as six on a scale of one to ten, where one is low price and ten is high price."

"Data Factory is expensive."

"I would not say that this product is overly expensive."

"Product is priced at the market standard."

"The price is fair."

More Azure Data Factory pricing and cost advice

"It's really good value for the money. There are some things they could improve on, but in terms of the pricing, features, and support, as a holistic package, we are not thinking of anything else at this point in time."

"It is not as expensive as Oracle GoldenGate and has worked really well within our budgets."

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Top Industries

By visitors reading reviews

Financial Services Firm

13%

Computer Software Company

12%

Manufacturing Company

Healthcare Company

Financial Services Firm

20%

Computer Software Company

13%

Manufacturing Company

Real Estate/Law Firm

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

Questions from the Community

How do you select the right cloud ETL tool?

AWS Glue and Azure Data factory for ELT best performance cloud services.

See all answers

How does Azure Data Factory compare with Informatica PowerCenter?

Azure Data Factory is flexible, modular, and works well. In terms of cost, it is not too pricey. It offers the stability and reliability I am looking for, good scalability, and is easy to set up an...

See all answers

How does Azure Data Factory compare with Informatica Cloud Data Integration?

Azure Data Factory is a solid product offering many transformation functions; It has pre-load and post-load transformations, allowing users to apply transformations either in code by using Power Q...

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Comparisons

Informatica PowerCenter vs Azure Data Factory

Compared 13% of the time

Snowflake vs Azure Data Factory

Compared 10% of the time

Informatica Intelligent Data Management Cloud (IDMC) vs Azure Data Factory

Compared 8% of the time

Alteryx Designer vs Azure Data Factory

Compared 7% of the time

IBM InfoSphere DataStage vs Azure Data Factory

Compared 4% of the time

More Azure Data Factory Competitors

Oracle GoldenGate vs Quest SharePlex

Compared 67% of the time

Qlik Replicate vs Quest SharePlex

Compared 14% of the time

AWS Database Migration Service vs Quest SharePlex

Compared 8% of the time

Fivetran vs Quest SharePlex

Compared 6% of the time

IBM App Connect vs Quest SharePlex

Compared 5% of the time

More Quest SharePlex Competitors

Product Reports

Buyer's Guide

Azure Data Factory

December 2024

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Buyer's Guide

Quest SharePlex

December 2024

Download Quest SharePlex product report

Also Known As

No data available

Dell SharePlex, SharePlex

Learn More

Microsoft

Quest Software

Overview

Azure Data Factory efficiently manages and integrates data from various sources, enabling seamless movement and transformation across platforms. Its valuable features include seamless integration with Azure services, handling large data volumes, flexible transformation, user-friendly interface, extensive connectors, and scalability. Users have experienced improved team performance, workflow simplification, enhanced collaboration, streamlined processes, and boosted productivity.

SharePlex database replication empowers your organization to achieve its database goals now and into the future. Make use of built-in monitoring, conflict resolution, data comparison and synchronization capabilities backed by award-winning support.

Sample Customers

1. Adobe 2. BMW 3. Coca-Cola 4. General Electric 5. Johnson & Johnson 6. LinkedIn 7. Mastercard 8. Nestle 9. Pfizer 10. Samsung 11. Siemens 12. Toyota 13. Unilever 14. Verizon 15. Walmart 16. Accenture 17. American Express 18. AT&T 19. Bank of America 20. Cisco 21. Deloitte 22. ExxonMobil 23. Ford 24. General Motors 25. IBM 26. JPMorgan Chase 27. Microsoft (Azure Data Factory is developed by Microsoft) 28. Oracle 29. Procter & Gamble 30. Salesforce 31. Shell 32. Visa

Bodybuilding.com, Priceline.com, Ameco Beijing, Viasat, SK Broadband

Buyer's Guide

Azure Data Factory vs. Quest SharePlex

December 2024

Free Report: Azure Data Factory vs. Quest SharePlex

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