Azure Data Factory vs SharePlex comparison

Microsoft and Quest Software are both solutions in the Data Integration category. Microsoft is ranked #5 with an average rating of 7.9, while Quest Software is ranked #48. Microsoft holds a 2.3% mindshare in DI, compared to Quest Software’s 1.1% 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 96 Azure Data Factory reviews

14,099 Views
9,728 Comparison Views

92% willing to recommend

SharePlex

Read 5 SharePlex reviews

3,693 Views
2,400 Comparison Views

100% willing to recommend

Azure Data Factory

SharePlex

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Executive SummaryUpdated on Mar 1, 2026

SharePlex and Azure Data Factory are in the data management and transformation category. Azure Data Factory appears to have the upper hand due to its robust feature set and integration capabilities.

Features: SharePlex delivers strong replication, particularly for Oracle databases, with features like its Compare and Repair tool and PEP for efficient data management. Azure Data Factory supports extensive data transformations and offers integration with Azure services, featuring a user-friendly interface, a large number of built-in connectors, and a comprehensive suite for complex workflows.

Room for Improvement: SharePlex could benefit from enhanced flexibility and broader database support beyond Oracle. Its interface may need modernization to match current standards. Updates for integration with cloud services could improve its competitiveness. Azure Data Factory's learning curve is initially steep for new users. More detailed error tracking and enhanced documentation could improve usability. Additional pricing transparency might clarify cost expectations for potential users.

Ease of Deployment and Customer Service: SharePlex offers a straightforward deployment process with tailored support for Oracle environments. Azure Data Factory, integrated with the broader Azure ecosystem, provides a cloud-centric deployment that requires some learning but is supported by robust customer service and rich online resources.

Pricing and ROI: SharePlex is known for cost-effectiveness, especially in replication-focused environments, yielding excellent ROI. Azure Data Factory, with potentially higher initial costs, offers substantial ROI through its extensive features and integration capabilities, making it an attractive investment for large-scale operations and long-term data strategies.

To learn more, read our detailed Azure Data Factory vs. SharePlex Report (Updated: August 2026).

Buyer's Guide

Azure Data Factory vs. SharePlex

August 2026

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Review summaries and opinions

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

Categories and Ranking

Azure Data Factory

Ranking in Data Integration

5th

Average Rating

8.0

Reviews Sentiment

6.7

Number of Reviews

Ranking in other categories

Cloud Data Warehouse (7th)

SharePlex

Ranking in Data Integration

48th

Average Rating

9.0

Reviews Sentiment

7.3

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of August 2026, in the Data Integration category, the mindshare of Azure Data Factory is 2.3%, down from 7.2% compared to the previous year. The mindshare of SharePlex is 1.1%, up from 0.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration Mindshare Distribution
Product	Mindshare (%)
Azure Data Factory	2.3%
SharePlex	1.1%
Other	96.6%

Data Integration

Featured Reviews

KandaswamyMuthukrishnan

Director at a computer software company with 1,001-5,000 employees

Integrates diverse data sources and streamlines ETL processes effectively

Regarding potential areas of improvement for Azure Data Factory, there is a need for better data transformation, especially since many people are now depending on DataBricks more for connectivity and data integration. Azure Data Factory should consider how to enhance integration or filtering for more transformations, such as integrating with Spark clusters. I am satisfied with Azure Data Factory so far, but I suggest integrating some AI functionality to analyze data during the transition itself, providing insights such as null records, common records, and duplicates without running a separate pipeline or job. The monitoring tools in Azure Data Factory are helpful for optimizing data pipelines; while the current feature is adequate, they can improve by creating a live dashboard to see the online process, including how much percentage has been completed, which will be very helpful for people who are monitoring the pipeline.

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Abhijit Arun Gujare

Sr. Oracle DBA at a comms service provider with 10,001+ employees

Real-time replication means our data is available almost instantaneously if an issue occurs in one of our data centers

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. We have discussed this and they have said it is in their future pipeline, but not with a definite date at which we will see this type of feature.

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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 flexibility that Azure Data Factory offers is great."

"It's extremely consistent."

"Data Factory's best features are connectivity with different tools and focusing data ingestion using pipeline copy data."

"The interface of Azure Data Factory is very usable with a more interactive visual experience, making it easier for people who are not as experienced in coding to work with."

"It makes it easy to collect data from different sources."

"The most valuable feature is the ease in which you can create an ETL pipeline."

"Instead of individual people reviewing these files, we were able to automate the ingestion process, which saved a bunch of time and hours of repeated manual work."

"The solution can scale very easily."

More Azure Data Factory pros

"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 synchronization, data backup, and data transfer are all valuable features of the solution."

"Try it out in your production and you won't be disappointed."

"SharePlex has been a good fit for us because it was not as expensive compared to GoldenGate, it was stable compared to AWS DMS, and it was a good product for what we were looking for and within our budget too."

"It works 100 percent of the time, with little downtime or problems."

"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."

"I like SharePlex's Compare and Repair tool."

More SharePlex pros

Cons

"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."

"The only thing that we're struggling with is increasing the competency of my team, so we think that the Microsoft documentation is too complicated."

"Real-time replication is required, and this is not a simple task."

"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."

"As far as customer service and support with Azure Data Factory, we are not always satisfied with the response time."

"I have not found any real shortcomings within the product."

"Azure Data Factory's pricing in terms of utilization could be improved."

"The product could provide more ways to import and export data."

More Azure Data Factory cons

"The reporting features need improvement."

"I don't know how easy it would be to change the architecture in an already implemented replication."

"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 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."

"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."

"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 the solution to have some kind of machine learning and AI capabilities."

"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."

Pricing and Cost Advice

"Data Factory is affordable."

"The licensing is a pay-as-you-go model, where you pay for what you consume."

"The pricing is a bit on the higher end."

"Product is priced at the market standard."

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

"The solution is cheap."

"In terms of licensing costs, we pay somewhere around S14,000 USD per month. There are some additional costs. For example, we would have to subscribe to some additional computing and for elasticity, but they are minimal."

"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

11%

Manufacturing Company

Computer Software Company

Construction Company

13%

Financial Services Firm

Manufacturing Company

Healthcare Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	31
Midsize Enterprise	21
Large Enterprise	63

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

Snowflake vs Azure Data Factory

Compared 4% of the time

Databricks vs Azure Data Factory

Compared 4% of the time

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

Compared 4% of the time

Palantir Foundry vs Azure Data Factory

Compared 3% of the time

Oracle Data Integrator (ODI) vs Azure Data Factory

Compared 3% of the time

More Azure Data Factory Competitors

Oracle Data Integrator (ODI) vs SharePlex

Compared 10% of the time

SSIS vs SharePlex

Compared 6% of the time

Informatica PowerCenter vs SharePlex

Compared 6% of the time

Oracle GoldenGate vs SharePlex

Compared 6% of the time

Qlik Replicate vs SharePlex

Compared 4% of the time

More SharePlex Competitors

Product Reports

Buyer's Guide

Azure Data Factory

August 2026

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Buyer's Guide

SharePlex

July 2026

Download SharePlex product report

Also Known As

No data available

Dell SharePlex, SharePlex

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.

Microsoft

SharePlex delivers robust database replication and migration capabilities, emphasizing performance, synchronization, and data integrity management. Supporting high availability and real-time data syncing, it serves organizations handling vast transaction volumes, especially in IoT data processing.

SharePlex offers reliable data transfer and efficient multi-target replication. Its features like Compare and Repair utilities assist in maintaining data consistency. With PEP fostering scalability for large transactions, it caters to businesses aiming to cut down migration windows and minimize outages. Users employ SharePlex in real-time syncing and failover scenarios across data centers, crucial for handling extensive transaction data during migrations or upgrades.

What are SharePlex's key features?

Core Replication: Ensures reliable data synchronization across multiple targets.
Data Integrity Management: Maintains accuracy during reading and writing processes.
Compare and Repair Utilities: Facilitate data consistency checks and fixes.
PEP: Enhances performance for large transaction volumes.

Why consider SharePlex for your database needs?

Scalability: Supports large-scale transactions with efficiency.
Minimized Downtime: Provides continuous data availability during operations.
Business Continuity: Enables seamless failover and data center transitions.
Real-time Syncing: Supports time-sensitive data processing requirements.

Organizations in sectors like finance and telecommunications implement SharePlex to maintain uninterrupted operations and ensure quick recovery times. By facilitating database migrations to cloud platforms like AWS, they achieve reduced downtime and enhanced operational efficiency, catering to the rigorous demands of data-driven industries.

Quest Software

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. SharePlex

August 2026

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