Oracle Data Integrator (ODI) vs Spring Cloud Data Flow comparison

Oracle and Broadcom are both solutions in the Data Integration category. Oracle is ranked #10 with an average rating of 7.6, while Broadcom is ranked #31 with an average rating of 7.5. Oracle holds a 2.6% mindshare in DI, compared to Broadcom’s 1.0% mindshare. Additionally, 84% of Oracle users are willing to recommend the solution, compared to 88% of Broadcom users who would recommend it.

Oracle Data Integrator (ODI)

Read 73 Oracle Data Integrator (ODI) reviews

11,239 Views
7,305 Comparison Views

84% willing to recommend

Spring Cloud Data Flow

Read 9 Spring Cloud Data Flow reviews

4,093 Views
2,251 Comparison Views

88% willing to recommend

Oracle Data Integrator (ODI)

Spring Cloud Data Flow

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Executive SummaryUpdated on Jun 3, 2026

Oracle Data Integrator and Spring Cloud Data Flow compete in the data integration and ETL/EL-T solutions category. Spring Cloud Data Flow appears to have the upper hand due to its real-time capabilities and adaptability with microservices while offering simplified and auto-configured processes that enhance user experience.

Features: Oracle Data Integrator uses an EL-T approach that leverages target data servers for transformations, significantly enhancing integration projects by minimizing staging needs. It supports a range of technologies like RDBMS, Hadoop, and cloud services, offering extensive flexibility. Knowledge Modules allow customization and automation, enriching productivity and integration. Spring Cloud Data Flow is highly valued for real-time task management and seamless integration with microservices, allowing rapid deployment. Its auto-configuration and flexibility in setting up complex data flows simplify operations, providing ease of orchestration in cloud environments.

Room for Improvement: ODI users seek better error handling, simplification of its application use, and enhanced integration with Oracle Analytics Services. There's also a need for less complex reverse engineering and improved metadata management. Spring Cloud Data Flow users would benefit from stronger community support, improved Kubernetes integration, and more comprehensive documentation for complex deployment configurations. Both solutions can improve their user interfaces for handling complex workflows more intuitively.

Ease of Deployment and Customer Service: ODI offers robust deployment options in on-premises and hybrid cloud settings but can be complex to set up initially. Customer service quality varies, with some users seeking faster response times although the support is knowledgeable. Spring Cloud Data Flow excels in orchestrating microservices and is primarily deployed in private and on-premises clouds. It's praised for quick issue resolution from its technical team, though limited community support sometimes hinders problem-solving.

Pricing and ROI: ODI is usually seen as expensive due to its deployment and usage models, potentially making it costly for smaller businesses but manageable for mid-sized ones with adequate long-term savings through automation. Spring Cloud Data Flow's open-source version offers significant savings and value, although additional support services incur costs. Both solutions offer potential for substantial ROI, but cost-effectiveness varies based on scale and specific deployment needs.

To learn more, read our detailed Oracle Data Integrator (ODI) vs. Spring Cloud Data Flow Report (Updated: June 2026).

Buyer's Guide

Oracle Data Integrator (ODI) vs. Spring Cloud Data Flow

June 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

Oracle Data Integrator (ODI)

Ranking in Data Integration

10th

Average Rating

8.0

Reviews Sentiment

6.7

Number of Reviews

Ranking in other categories

No ranking in other categories

Spring Cloud Data Flow

Ranking in Data Integration

31st

Average Rating

7.8

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

Streaming Analytics (17th)

Mindshare comparison

As of July 2026, in the Data Integration category, the mindshare of Oracle Data Integrator (ODI) is 2.6%, down from 4.3% compared to the previous year. The mindshare of Spring Cloud Data Flow is 1.0%, down from 1.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration Mindshare Distribution
Product	Mindshare (%)
Oracle Data Integrator (ODI)	2.6%
Spring Cloud Data Flow	1.0%
Other	96.4%

Data Integration

Featured Reviews

Hafiz Mannan

Head of Data Services – Services Partner at 3 As Technologies

Facilitates complex data integration with ease and flexibility

It would be great if ODI could link the designer, mapping, and workflows in a more simplified manner, maybe in one combined interface. 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 instead of having the designer separately, mapping separately, and monitoring and session management separately. With respect to data quality challenges, it would be great to give an option to fix data quality issues based on AI. Integrating AI with ODI that provides recommendations on how to fix those data quality issues after analyzing and profiling business data would be excellent. One of the main disadvantages of the Oracle Data Integrator (ODI) is that it sometimes takes a lot of resources when handling multiple jobs. The scalability and the ability to handle multiple workloads of several parallel ETL jobs could use improvement, and certain parallel threads should be added along with the ability to configure multiple jobs from the same data directory structure.

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NitinGoyal

Engineering Lead at Naukri.com

Has a plug-and-play model and provides good robustness and scalability

The solution's community support could be improved. I don't know why the Spring Cloud Data Flow community is not very strong. Community support is very limited whenever you face any problem or are stuck somewhere. I'm not sure whether it has improved in the last six months because this pipeline was set up almost two years ago. I struggled with that a lot. For example, there was limited support whenever I got an exception and sought help from Stack Overflow or different forums. Interacting with Kubernetes needs a few certificates. You need to define all the certificates within your application. With the help of those certificates, your Java application or Spring Cloud Data Flow can interact with Kubernetes. I faced a lot of hurdles while placing those certificates. Despite following the official documentation to define all the replicas, readiness, and liveliness probes within the Spring Cloud Data Flow application, it was not working. So, I had to troubleshoot while digging in and debugging the internals of Spring Cloud Data Flow at that time. It was just a configuration mismatch, and I was doing nothing weird. There was a small spelling difference between how Spring Cloud Data Flow was expecting it and how I passed it. I was just following the official documentation.

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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

"It can integrate with more recent databases like Cassandra, Hadoop, and other more recent Big Data databases."

"For us, ODI has been key in collecting, transforming, and storing information from our various sources."

"We spend much less time developing integrations because all we need to focus on is the business logic."

"The most valuable feature of ODI is the to use of the whole ETL to create a data lake."

"I found nothing overly amazing about this tool, although I appreciate its ability to easily load slowly changing dimensions."

"The most valuable features of ODI are the ease of development, you can have a template, and you can onboard transfer very quickly."

"It is a clever integration tool to extract data from every possible source, and it can transform the source data to a format the targets can handle."

"Far more efficient and robust than OWB, (it was the natural evolution for us)."

More Oracle Data Integrator (ODI) pros

"Overall, Spring Cloud Data Flow is a really good solution and a lot cheaper than a lot of infrastructure provided by big companies like Google or Amazon."

"This product will assist us in saving costs in many ways: No longer need to continue paying high fees for proprietary software, reduce the number of software engineers needed to support the product, and achieve faster time to market by using this product for our middleware."

"The most valuable features of Spring Cloud Data Flow are the simple programming model, integration, dependency Injection, and ability to do any injection. Additionally, auto-configuration is another important feature because we don't have to configure the database and or set up the boilerplate in the database in every project. The composability is good, we can create small workloads and compose them in any way we like."

"The best thing I like about Spring Cloud Data Flow is its plug-and-play model."

"The dashboards in Spring Cloud Dataflow are quite valuable."

"The most valuable feature is real-time streaming."

"There are a lot of options in Spring Cloud. It's flexible in terms of how we can use it. It's a full infrastructure."

"The ease of deployment on Kubernetes, the seamless integration for orchestration of various pipelines, and the visual dashboard that simplifies operations even for non-specialists such as quality analysts."

More Spring Cloud Data Flow pros

Cons

"I rate it a seven out of 10 because there is room for growth because ODI is still new, in comparison to Informatica, which is a mature product."

"If there was an add-on tool to hide the performance issues and solve them for me, then I might be interested in that as it would provide me value."

"The Oracle Data Integrator interface is extremely slow, especially when using remote desktop connections."

"The initial setup is a bit complex compared to other tools."

"It would be really good if Oracle considered enabling the tool to integrate with some other platforms that are deprecated simply for commercial reasons"

"Overall performance needs improvement. Especially when running ODI clients on Windows desktops."

"It lacks a suite of tools suitable for fully processing data and moving it into decision support warehouses."

"They need to work on the multiuser development environment and include the ability to comply with different kinds of SDLCs."

More Oracle Data Integrator (ODI) cons

"There were instances of deployment pipelines getting stuck, and the dashboard not always accurately showing the application status, requiring manual intervention such as rerunning applications or refreshing the dashboard."

"The documentation on offer is not that good."

"The visual user interface could use some help; it needs improvement."

"Spring Cloud Data Flow is not an easy-to-use tool, so improvements are required."

"Some of the features, like the monitoring tools, are not very mature and are still evolving."

"The solution's community support could be improved."

"I would improve the dashboard features as they are not very user-friendly."

"Spring Cloud Data Flow could improve the user interface. We can drag and drop in the application for the configuration and settings, and deploy it right from the UI, without having to run a CI/CD pipeline. However, that does not work with Kubernetes, it only works when we are working with jars as the Spring Cloud Data Flow applications."

More Spring Cloud Data Flow cons

Pricing and Cost Advice

"Being an ODI developer, I never had to pay for this product. I know that the pricing/licensing is not really low, but the product is really good."

"The Oracle Data Integrator (ODI) pricing isn't expensive, but it's not cheap, so it's in the middle. I'd rate the pricing as three out of five."

"The solution is expensive because of the model they use. The cost is for the license and for support."

"The license can be costly, but in certain complex cases, ODI proves to be the optimal solution."

"We found that the cost compared to other integration tools is a little high, but the solution works great."

"I have yet to determine the exact figure for Oracle Data Integrator (ODI) pricing, but it has lower pricing than Informatica."

"I rate the platform pricing as five out of ten."

"There is a standard license to use the solution but there are other costs in addition, such as hardware and operating system."

More Oracle Data Integrator (ODI) pricing and cost advice

"This is an open-source product that can be used free of charge."

"The solution provides value for money, and we are currently using its community edition."

"If you want support from Spring Cloud Data Flow there is a fee. The Spring Framework is open-source and this is a free solution."

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Top Industries

By visitors reading reviews

Financial Services Firm

14%

Government

Manufacturing Company

Outsourcing Company

Financial Services Firm

17%

Computer Software Company

10%

Retailer

Outsourcing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	26
Midsize Enterprise	12
Large Enterprise	44

By reviewers
Company Size	Count
Small Business	3
Midsize Enterprise	1
Large Enterprise	5

Questions from the Community

What's the difference between Oracle Integration Cloud Service and Oracle Data Integrator (ODI)?

Oracle Integration Cloud Service has a fairly easy initial setup, and Oracle offers initial support and guidance for those who might find the setup to be challenging. There are complications that c...

See all answers

What do you like most about Oracle Data Integrator (ODI)?

In comparison with other products of the same range, licensing mode is really attractive, no need to license according technology/topology to be used and an incredible Versatility to build any Data...

See all answers

What is your experience regarding pricing and costs for Oracle Data Integrator (ODI)?

I need two administrators for Oracle Data Integrator (ODI).

See all answers

What needs improvement with Spring Cloud Data Flow?

There were instances of deployment pipelines getting stuck, and the dashboard not always accurately showing the application status, requiring manual intervention such as rerunning applications or r...

See all answers

What is your primary use case for Spring Cloud Data Flow?

We had a project for content management, which involved multiple applications each handling content ingestion, transformation, enrichment, and storage for different customers independently. We want...

See all answers

What advice do you have for others considering Spring Cloud Data Flow?

I would definitely recommend Spring Cloud Data Flow. It requires minimal additional effort or time to understand how it works, and even non-specialists can use it effectively with its friendly docu...

See all answers

Comparisons

Oracle Integration Cloud Service vs Oracle Data Integrator (ODI)

Compared 22% of the time

Informatica PowerCenter vs Oracle Data Integrator (ODI)

Compared 5% of the time

SSIS vs Oracle Data Integrator (ODI)

Compared 4% of the time

Pentaho Data Integration and Analytics vs Oracle Data Integrator (ODI)

Compared 3% of the time

SharePlex vs Oracle Data Integrator (ODI)

Compared 3% of the time

More Oracle Data Integrator (ODI) Competitors

Apache Flink vs Spring Cloud Data Flow

Compared 10% of the time

Cloudera DataFlow vs Spring Cloud Data Flow

Compared 5% of the time

TIBCO Spotfire vs Spring Cloud Data Flow

Compared 5% of the time

TIBCO BusinessWorks vs Spring Cloud Data Flow

Compared 4% of the time

StreamSets vs Spring Cloud Data Flow

Compared 4% of the time

More Spring Cloud Data Flow Competitors

Product Reports

Buyer's Guide

Oracle Data Integrator (ODI)

July 2026

Download Oracle Data Integrator (ODI) product report

Buyer's Guide

Spring Cloud Data Flow

July 2026

Download Spring Cloud Data Flow product report

Also Known As

ODI

No data available

Overview

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?

EL-T Architecture: Optimizes data processing by leveraging database capabilities
Knowledge Modules: Customizable strategies for faster development
Integration Support: Handles RDBMS, cloud, and big data
Automation: Facilitates rapid deployment and transformations
Real-Time Data Warehousing: Supports continuous data integration

What benefits and ROI should users consider?

Flexibility: Adapts to multiple data integration needs
Efficiency: Leverages existing database engines for optimal ETL functionalities
Scalability: Manages complex, large-scale environments
Cost-Effectiveness: Supports diverse data sources and technology platforms

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.

Oracle

Spring Cloud Data Flow is a toolkit for building data integration and real-time data processing pipelines.
Pipelines consist of Spring Boot apps, built using the Spring Cloud Stream or Spring Cloud Task microservice frameworks. This makes Spring Cloud Data Flow suitable for a range of data processing use cases, from import/export to event streaming and predictive analytics. Use Spring Cloud Data Flow to connect your Enterprise to the Internet of Anything—mobile devices, sensors, wearables, automobiles, and more.

Broadcom

Sample Customers

Griffith University, Kansas City Power & Light, Keste, Raymond James Financial, Valdosta State University

Information Not Available

Buyer's Guide

Oracle Data Integrator (ODI) vs. Spring Cloud Data Flow

June 2026

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