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Compare Azure Data Factory vs. Oracle Autonomous Data Warehouse

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Featured Review
Find out what your peers are saying about Azure Data Factory vs. Oracle Autonomous Data Warehouse and other solutions. Updated: November 2021.
552,305 professionals have used our research since 2012.
Quotes From Members

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

Pros
"Powerful but easy-to-use and intuitive.""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.""From what we have seen so far, the solution seems very stable.""Azure Data Factory's most valuable features are the packages and the data transformation that it allows us to do, which is more drag and drop, or a visual interface. So, that eases the entire process.""The best part of this product is the extraction, transformation, and load.""The solution can scale very easily.""It's extremely consistent.""It is easy to integrate."

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"The analytics have been very good. We've found them to be quite useful.""The solution is self-securing. All data is encrypted and security updates and patches are applied automatically both periodically and off-cycle.""It provides Transparent Data Encryption (TDE) capabilities by default to address data security issues.""The solution integrates well with Power BI.""The performance and scalability are awesome.""Self-patching and runs machine-learning across its logs all the time"

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Cons
"The Microsoft documentation is too complicated.""The pricing scheme is very complex and difficult to understand.""Azure Data Factory should be cheaper to move data to a data center abroad for calamities in case of disasters.""The solution needs to integrate more with other providers and should have a closer integration with Oracle BI.""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.""My only problem is the seamless connectivity with various other databases, for example, SAP.""We are too early into the entire cycle for us to really comment on what problems we face. We're mostly using it for transformations, like ETL tasks. I think we are comfortable with the facts or the facts setting. But for other parts, it is too early to comment on."

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"One of the major problem is creating custom tablespace. The ADB serverless option doesn't support custom tablespace creation, which could cause issues during on-premise database migration that requires specifically named tablespace. There should be an option to create customized tablespace.""The initial setup was pretty complex. It was not easy.""Sometimes the solution works differently between the cloud and on-premises. It needs to be more consistent and predictable.""The solution could be improved by allowing for migration tools from other cloud services, including migration from Amazon Redshift, RDS, and Aurora.""It is very important the integration with other platforms be made to be as easy as it is with an on-premises deployment.""Ease of connectivity could be improved."

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Pricing and Cost Advice
"This is a cost-effective solution.""The licensing is a pay-as-you-go model, where you pay for what you consume.""It's not particularly expensive.""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.""Our licensing fees are approximately 15,000 ($150 USD) per month.""Understanding the pricing model for Data Factory is quite complex.""I would not say that this product is overly expensive.""The licensing cost is included in the Synapse."

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"You pay as you go, and you don't pay for services that you don't use.""ROI is high."

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Questions from the Community
Top Answer: AWS Glue and Azure Data factory for ELT best performance cloud services.
Top Answer: 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 and… more »
Top Answer: 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… more »
Top Answer: The performance and scalability are awesome.
Top Answer: You pay as you go, and you don't pay for services that you don't use. If you feel that you need additional resources then you can increase them and pay only for them. There is no need to worry about… more »
Top Answer: It is very important the integration with other platforms be made to be as easy as it is with an on-premises deployment. On-premises, you can integrate with different vendors such as Microsoft. There… more »
Ranking
3rd
Views
26,751
Comparisons
21,970
Reviews
24
Average Words per Review
494
Rating
7.7
6th
Views
5,208
Comparisons
3,937
Reviews
6
Average Words per Review
538
Rating
8.3
Comparisons
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Overview

Create, schedule, and manage your data integration at scale with Azure Data Factory - a hybrid data integration (ETL) service. Work with data wherever it lives, in the cloud or on-premises, with enterprise-grade security.

Autonomous Data Warehouse is market-leading Oracle Database software running on proven Oracle Exadata infrastructure that is optimized to deliver unbeatable performance for data warehouse workloads. Built-in adaptive machine learning eliminates manual labor for administrative management. With Oracle, business and enterprise users can now build their own data warehouse, data mart, or sandbox in a few minutes.

Offer
Learn more about Azure Data Factory
Learn more about Oracle Autonomous Data Warehouse
Sample Customers
Milliman, Pier 1 Imports, Rockwell Automation, Ziosk, Real Madrid
Hertz, TaylorMade Golf, Outront Media, Kingold, FSmart, Drop-Tank
Top Industries
REVIEWERS
Computer Software Company31%
Insurance Company13%
Healthcare Company6%
Logistics Company6%
VISITORS READING REVIEWS
Computer Software Company32%
Comms Service Provider14%
Financial Services Firm6%
Energy/Utilities Company6%
VISITORS READING REVIEWS
Computer Software Company47%
Comms Service Provider12%
Government4%
Financial Services Firm4%
Company Size
REVIEWERS
Small Business24%
Midsize Enterprise29%
Large Enterprise47%
VISITORS READING REVIEWS
Small Business17%
Midsize Enterprise8%
Large Enterprise75%
REVIEWERS
Small Business44%
Large Enterprise56%
Find out what your peers are saying about Azure Data Factory vs. Oracle Autonomous Data Warehouse and other solutions. Updated: November 2021.
552,305 professionals have used our research since 2012.

Azure Data Factory is ranked 3rd in Cloud Data Warehouse with 25 reviews while Oracle Autonomous Data Warehouse is ranked 6th in Cloud Data Warehouse with 6 reviews. Azure Data Factory is rated 7.8, while Oracle Autonomous Data Warehouse is rated 8.6. The top reviewer of Azure Data Factory writes "Easy to bring in outside capabilities, flexible, and works well". On the other hand, the top reviewer of Oracle Autonomous Data Warehouse writes "Self-patching means I generally don't need a DBA; detailed analytics make it very capable". Azure Data Factory is most compared with Informatica PowerCenter, Talend Open Studio, Informatica Cloud Data Integration, Palantir Foundry and Denodo, whereas Oracle Autonomous Data Warehouse is most compared with Snowflake, Microsoft Azure Synapse Analytics, Amazon Redshift, Oracle Exadata and VMware Tanzu Greenplum. See our Azure Data Factory vs. Oracle Autonomous Data Warehouse report.

See our list of best Cloud Data Warehouse vendors.

We monitor all Cloud Data Warehouse reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.