Spring Cloud Data Flow vs Teradata comparison

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Spring Cloud Data Flow

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Executive SummaryUpdated on Jul 27, 2025

Teradata and Spring Cloud Data Flow operate in the data management and analytics space. Teradata often has the advantage in handling vast data volumes and complex analytical tasks, thanks to its speed and scalability.

Features: Teradata is known for its speed, parallel processing, and advanced workload management. It handles large data volumes effectively and supports a wide range of analytics. Spring Cloud Data Flow is flexible with integration capabilities and is user-friendly for managing microservices and real-time data flows, especially for real-time analytics and microservice orchestration.

Room for Improvement: Teradata could improve in terms of cost, modern user interfaces, and handling unstructured data. Spring Cloud Data Flow needs enhancements in documentation clarity, community support, and user interface to improve troubleshooting and user experience.

Ease of Deployment and Customer Service: Teradata offers various deployment options but is often criticized for its cost and complexity in cloud environments. Its customer service is noted for technical expertise, though response times can be slow. Spring Cloud Data Flow's open-source nature allows flexible integration but struggles with sufficient support and extensive documentation.

Pricing and ROI: Teradata's pricing is considered high, and users must justify costs through notable performance benefits and ROI, appealing mainly to large organizations needing extensive data capabilities. Spring Cloud Data Flow's open-source model makes it cost-effective, appealing to organizations looking for budget-friendly solutions. ROI for both options depends on specific use cases and business needs.

To learn more, read our detailed Spring Cloud Data Flow vs. Teradata Report (Updated: July 2025).

Spring Cloud Data Flow vs. Teradata

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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

Spring Cloud Data Flow

Ranking in Data Integration

20th

Average Rating

7.8

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

Streaming Analytics (9th)

Teradata

Ranking in Data Integration

15th

Average Rating

8.2

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

Customer Experience Management (6th), Backup and Recovery (20th), Relational Databases Tools (8th), Data Warehouse (3rd), BI (Business Intelligence) Tools (9th), Marketing Management (6th), Cloud Data Warehouse (4th)

Mindshare comparison

As of August 2025, in the Data Integration category, the mindshare of Spring Cloud Data Flow is 1.3%, up from 0.9% compared to the previous year. The mindshare of Teradata is 1.2%, up from 0.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration

Featured Reviews

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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RajeshKumar25

Principal Consultant & Director at Quensulting

Harnessing advanced parallelism for top performance while embracing cloud trends

Teradata is primarily used for data warehousing across all customers. My clients have built-in applications that use Teradata, and their use varies from customer to customer, depending on the industry and database size. The primary function is as an OLAP analytical ecosystem Scalability is…

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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 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 solution's most valuable feature is that it allows us to use different batch data sources, retrieve the data, and then do the data processing, after which we can convert and store it in the target."

"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."

"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 product is very user-friendly."

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

"It's very mature from a technology perspective."

"I like writing preformance queries for preprocessing on AWS Cloud."

"It has reduced a lot of reworking on maintaining indexes, partitions, etc."

"It is a highly robust software solution."

"When it comes to integration, tools like Informatica seamlessly connect with Teradata. We ensure the Teradata database is configured correctly in Informatica, including the proper hostname and properties for the load process. We didn't find any major complexity or issues with integration."

"We did performance testing. We had a set of real life MicroStrategy reports. Our conditions were: Not allowed to redesign data model, not allowed to rewrite the queries, all queries should be generated by MicroStrategy, no aggregates. Teradata appeared to be way faster than a similarly configured (in terms of hardware) Oracle server."

"I've never had any issues with scalability."

"Parallel processing features have helped to easily dump any size of data and retrieve data with great performance."

More Teradata pros

Cons

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

"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."

"On the tool's online discussion forums, you may get stuck with an issue, making it an area where improvements are required."

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

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

"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."

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

"The configurations could be better. Some configurations are a little bit time-consuming in terms of trying to understand using the Spring Cloud documentation."

"We tried to use case Teradata for a data warehouse system, but we had some problems in relation to the Teradata system, CDC tools, and source databases. We were unable to transfer data from HPE Integrity mainframe to Teradata."

"I would like to see an improved Knowledge Base on the web."

"The capability to implement it with comparable performance across various private cloud environments, ensuring adaptability to different infrastructure setups would be beneficial."

"It could use some more advanced analytics relating to structured and semi-structured data."

"Data synchronization to the DR site."

"There is some improvement required on OLTP level and some analytical function is missing."

"Teradata is somewhat late in adopting cloud technology."

"Teradata is a bit late for the cloud."

More Teradata cons

Pricing and Cost Advice

"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."

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

"I rate the product price a nine on a scale of one to ten, where one is cheap and ten is expensive."

"In this day and age, we want to get things done quickly. So, we go to the AWS Marketplace."

"Teradata pricing is fine, and it's competitive with all the legacy models. On a scale of one to five, with one being the worst and five being the best, I'm giving Teradata a three, because it can be a little expensive, when compared to other solutions."

"The solution requires a license."

"Teradata is a very expensive solution."

"When looking into implementing this product, pricing is the main issue followed by technical expertise."

"Teradata is expensive but gives value for money, especially if you don't want to move your data to the cloud."

"Teradata's licensing is on the expensive side."

More Teradata pricing and cost advice

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Comparison Review

it_user232068

Senior Data Architect at a pharma/biotech company with 1,001-5,000 employees

Aug 5, 2015

Netezza vs. Teradata

Original published at https://www.linkedin.com/pulse/should-i-choose-net Two leading Massively Parallel Processing (MPP) architectures for Data Warehousing (DW) are IBM PureData System for Analytics (formerly Netezza) and Teradata. I thought talking about the similarities and differences…

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Top Industries

By visitors reading reviews

Financial Services Firm

27%

Computer Software Company

16%

Retailer

Insurance Company

Financial Services Firm

26%

Computer Software Company

10%

Manufacturing Company

Healthcare Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

Questions from the Community

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...

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...

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...

Comparing Teradata and Oracle Database, which product do you think is better and why?

I have spoken to my colleagues about this comparison and in our collective opinion, the reason why some people may declare Teradata better than Oracle is the pricing. Both solutions are quite simi...

Which companies use Teradata and who is it most suitable for?

Before my organization implemented this solution, we researched which big brands were using Teradata, so we knew if it would be compatible with our field. According to the product's site, the comp...

Is Teradata a difficult solution to work with?

Teradata is not a difficult product to work with, especially since they offer you technical support at all levels if you just ask. There are some features that may cause difficulties - for example,...

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Product Reports

Spring Cloud Data Flow

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Also Known As

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IntelliFlex, Aster Data Map Reduce, , QueryGrid, Customer Interaction Manager, Digital Marketing Center, Data Mover, Data Stream Architecture

Overview

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.

VMware

Teradata is a scalable data analytics platform designed to meet enterprise demands for large-scale data management and processing, focusing on performance, scalability, and security for complex query executions.

As a leading data warehousing solution, Teradata integrates advanced analytics enabling organizations to derive insights from massive datasets. It supports high-volume data workloads with its architecture optimized for analytical queries. Users benefit from its robust scalability, allowing seamless expansion as data grows. Teradata's SQL engine is compatible with a wide range of data types, ensuring flexibility in data analysis. With advanced security measures, it protects sensitive data across various environments, providing peace of mind to users handling critical information.

What are the most important features of Teradata?

Linear Scalability: Easily expands data processing capabilities to handle increasing data loads without performance degradation.
Advanced Analytics: Supports complex analytical operations integrating machine learning and AI for predictive insights.
SQL Compatibility: Offers a comprehensive SQL interface that supports complex queries across diverse data types.
Data Security: Implements rigorous security protocols to protect data integrity and confidentiality.

What benefits and ROI should users look for?

Improved Decision-Making: Derive actionable insights quickly for strategic business decisions.
Cost Efficiency: Optimized resource usage reduces operational costs associated with data processing.
Increased Productivity: Streamlined data operations save time, allowing teams to focus on analysis.
Enhanced Scalability: Seamless growth without significant additional investment as data volumes increase.

Teradata is widely used in industries like finance, telecommunications, and healthcare, where data-driven decisions are critical. Companies leverage its robust analytics capabilities to enhance customer experiences, streamline operations, and ensure compliance with regulatory requirements. In these sectors, quick access to data insights can significantly impact competitive advantage.

Sample Customers

Information Not Available

Netflix

Spring Cloud Data Flow vs. Teradata