

Oracle Data Integrator (ODI) and Azure Data Factory compete in the data integration space. ODI takes the upper hand in handling complex data architectures due to its robust ELT capabilities and modularity while Azure Data Factory excels in its simplicity and cloud-native design.
Features: Oracle Data Integrator offers a powerful ELT architecture that supports complex environments, a range of Knowledge Modules for customization, and integration with cloud and ERP systems. Azure Data Factory provides flexible ETL processes focused on cloud integration, real-time processing via data flows, and strong connectivity within the Azure ecosystem.
Room for Improvement: Oracle Data Integrator faces challenges with complexity, the lack of SQL support for certain data types, and a steep learning curve. Improvements in error handling and better compatibility with other ETL tools are needed. Azure Data Factory struggles with performance during heavy processing and the need for more pre-built connectors, along with better integration with non-Microsoft platforms.
Ease of Deployment and Customer Service: Oracle Data Integrator is versatile across on-premises and hybrid environments but requires significant setup effort and has mixed support reviews. Azure Data Factory, cloud-based, offers an easy deployment experience focused on the Azure ecosystem with efficient customer service though limited to Microsoft solutions.
Pricing and ROI: Oracle Data Integrator is more expensive, offering several licensing options, with cost-saving potential within broader Oracle solutions. Azure Data Factory uses a pay-as-you-go model, providing cost-effectiveness for Azure-integrated services. Both solutions deliver solid ROI, with Oracle known for stable integration capabilities and Azure for cost efficiencies and operational agility.
Our stakeholders and clients have expressed satisfaction with Azure Data Factory's efficiency and cost-effectiveness.
On a scale of one to ten, I would rate the technical support as nine.
The technical support from Microsoft is rated an eight out of ten.
The technical support is responsive and helpful
I can get solutions quickly, and any tickets I submit to Oracle are responded to and resolved rapidly.
The technical support of Oracle is very good; they support the Oracle Data Integrator (ODI) solution effectively.
Azure Data Factory is highly scalable.
I did not experience scalability issues.
The scalability and the ability to handle multiple workloads of several parallel ETL jobs could use improvement.
The solution has a high level of stability, roughly a nine out of ten.
It gives me the accurate result.
I have been using Azure Data Factory for a very long time, and I did not find too many issues.
In terms of performance stability, I have not experienced any downtimes, crashes, or performance issues with the Oracle Data Integrator (ODI).
The ability to handle the largest volumes of data is another concern; if I have to manage more than one terabyte of data every day, I am not comfortable dealing with Azure Data Factory and had to switch to Oracle Data Integrators (ODI) because it lacks performance features.
If I am making a pipeline, it should give me suggestions, such as which activity should be used, so that I don't have to remember each activity.
Incorporating more dedicated API sources to specific services like HubSpot CRM or Salesforce would be beneficial.
If I use a source system like Oracle and a target system like Teradata, ODI will still run, but it struggles a bit with different infrastructures.
It would be excellent not to have to go into different areas to perform different activities but rather have a user-defined interface where we can configure a job, run it, monitor it, link packages, and link subprocesses all in one frame.
Adding AI capabilities would make Oracle Data Integrator (ODI) even better.
The pricing is cost-effective.
It is considered cost-effective.
ODI is cheaper compared to Informatica PowerCenter and IBM DataStage.
The pricing aspect of Oracle Data Integrator (ODI) is reasonable; it brings significant value to the table.
It connects to different sources out-of-the-box, making integration much easier.
The platform excels in handling major datasets, particularly when working with Power BI for reporting purposes.
Regarding the integration feature in Azure Data Factory, the integration part is excellent; we have major source connectors, so we can integrate the data from different data sources and also perform basic transformation while transforming, which is a great feature in Azure Data Factory.
The main benefits that Oracle Data Integrator (ODI) brings to the table include data quality, data completeness functionality, metadata management, and the reverse engineering feature, which allows integrating the metadata of diversified data sources with a single click.
Oracle Data Integrator (ODI) is powerful and strong if my system uses Oracle components for environments like OLTP, enterprise data warehouse, or data marts.
Oracle Data Integrator (ODI)'s ELT architecture has helped optimize my data movement and transformation significantly.
| Product | Mindshare (%) |
|---|---|
| Azure Data Factory | 2.2% |
| Oracle Data Integrator (ODI) | 3.0% |
| Other | 94.8% |


| Company Size | Count |
|---|---|
| Small Business | 31 |
| Midsize Enterprise | 21 |
| Large Enterprise | 64 |
| Company Size | Count |
|---|---|
| Small Business | 26 |
| Midsize Enterprise | 12 |
| Large Enterprise | 44 |
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.
Oracle Data Integrator offers flexible EL-T architecture, optimizing processing with database capabilities. It supports diverse data sources, automates deployment, and provides efficient data transformations, making it suitable for data warehousing and complex data environments.
Oracle Data Integrator leverages EL-T architecture to enhance processing by utilizing database strengths. It integrates with a wide array of technologies, including RDBMS, cloud, and big data. The software's Knowledge Modules enable customizable integration strategies, accelerating development. With a user-friendly interface and automation features, it simplifies metadata management and supports real-time data warehousing. Key areas such as UI performance, integration, and real-time data capabilities require enhancements. Challenges include error handling, initial setup, and compatibility with platforms like Git, Azure, and IoT services. Improvements in metadata management, scalability, and user-friendliness are needed.
What are the most important features of Oracle Data Integrator?Organizations utilize Oracle Data Integrator primarily in data warehousing, handling data from ERP systems, EBS, Fusion, and cloud databases. It aids in creating data lakes, OLTP migrations, digital health initiatives, and automation tasks, ensuring seamless integration with databases like MySQL and SQL Server.
We monitor all Data Integration 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.