Spring Cloud Data Flow vs Teradata comparison

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Spring Cloud Data Flow

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Executive SummaryUpdated on Apr 20, 2025

Teradata and Spring Cloud Data Flow are key players in data management and orchestration. Teradata appears to have the upper hand in handling complex queries and large-scale data warehousing tasks, whereas Spring Cloud Data Flow is noted for microservices deployment and ease of use.

Features: Teradata stands out for robust performance with massive parallel processing, shared-nothing architecture, and its ability to handle complex queries, making it reliable for high-volume data warehousing. Its scalability and advanced analytics capabilities are highly regarded. Spring Cloud Data Flow is praised for its ease of deploying and managing microservices, and real-time streaming. It integrates smoothly with various cloud platforms offering lower operational requirements and user-friendly features, which are ideal for environments focused on microservices and data flows.

Room for Improvement: Teradata faces challenges with high pricing and limitations in managing unstructured data. Cloud integration and on-premises scalability present further issues, with calls for a better user interface and technical support. Spring Cloud Data Flow struggles with weak community support, unclear documentation, and integration challenges with Kubernetes, rendering troubleshooting and diagnostics difficult for users.

Ease of Deployment and Customer Service: Teradata offers flexible deployment options across on-premises, private, and public clouds but can involve a complex deployment process and variable technical support. Spring Cloud Data Flow simplifies microservices deployment, especially in private clouds; however, its open-source nature often leaves users dependent on limited community resources for support.

Pricing and ROI: Teradata is recognized as a premium solution with a higher cost, although it delivers a positive ROI for large enterprises through superior performance and analytics. Its licensing remains costly compared to alternatives. Spring Cloud Data Flow, being open-source, provides a cost-effective deployment with potential additional support costs, offering value through efficiency and lower initial investment, appealing to businesses focused on cost-effectiveness.

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

21st

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 July 2025, in the Data Integration category, the mindshare of Spring Cloud Data Flow is 1.2%, up from 0.9% compared to the previous year. The mindshare of Teradata is 1.1%, 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 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 most valuable feature is real-time streaming."

"The product is very user-friendly."

"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 dashboards in Spring Cloud Dataflow are quite valuable."

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

"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."

"Teradata has good performance, the response times are very fast. Overall the solution is easy to use. When we do the transformation, we have all of our staging and aggregation data available."

"The two types of partitioning have been very significant for us - row and columnar partitioning."

"Teradata is a great, industry-leading data warehousing product that has MPP architecture."

"The flexibility in design is very good."

"It is a stable solution. Stability-wise, I rate the solution a nine out of ten."

"I like this solution's ease of design and the fact that its performance is quite good. It is stable as well."

"Auto-partitioning and indexing, and resource allocation on the fly are key features."

"The initial setup was straightforward."

More Teradata pros

Cons

"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."

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

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

"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 solution's community support could be improved."

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

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

"Teradata could improve by being less complicated. There are some aspects that are not available on the Unix server and a Unix system is required to access some data, such as in case of an emergency."

"I would like more security and speed."

"There is a need to improve performance in high transaction processes, as well as the reporting system."

"Data synchronization to the DR site."

"Teradata is an old data warehouse, and they're not improving in terms of new, innovative features."

"It needs a teaching web site with more training on third-party tools used for BI."

"Query language and its functionality are rather limited, compared to Oracle or even SQL Server. However, it is possible to perform any kind of logic in it (though some workarounds may be required)."

"I've been using the same UI for 20 years in Teradata. It could use some updating. Adding more stability around Teradata Studio would be outstanding. Teradata Studio is a Java-based version of their tool. It's much better now, but it still has some room for improvement."

More Teradata cons

Pricing and Cost Advice

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

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

"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."

"The cost of running Teradata is quite high, but you get a good return on investment."

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

"The tool costs about 30,000 euros a month, while Azure Synapse SQL only costs 10,000."

"Price is quite high, so if it is really possible to use other solutions (e.g. you do not have strict requirements for performance and huge data volumes), it might be better to look at alternatives from the RDBMS world."

"Users have to pay a yearly licensing fee for Teradata IntelliFlex, which is very expensive."

"The price of the solution could be reduced, it is expensive."

"It comes at a notably high cost for what it offers."

"The cost is substantial, totaling around $1.2 million, solely dedicated to upgrading the hardware."

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

26%

Computer Software Company

17%

Retailer

Manufacturing Company

Financial Services Firm

26%

Computer Software Company

11%

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

No data available

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