Spring Cloud Data Flow vs Teradata comparison

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Spring Cloud Data Flow

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Executive SummaryUpdated on Sep 30, 2025

Teradata and Spring Cloud Data Flow compete in the data management and orchestration space. Teradata seems to have the upper hand in performance capabilities, while Spring Cloud Data Flow offers strong real-time streaming and integration features.

Features: Teradata provides a robust data warehousing solution with parallel processing architecture and scalability. It offers a strong optimizer and workload management for enhanced system tuning, along with adaptability to various data environments. Its security features are well-regarded. Spring Cloud Data Flow excels in real-time streaming and orchestration capabilities. It boasts an easy integration with other services and has a user-friendly programming model. Its flexible deployment environment and ability to handle microservices are significant advantages.

Room for Improvement: Teradata users suggest improvements in transaction processing and integration with modern cloud environments. Enhancements in handling unstructured data and more competitive pricing structures are needed. Spring Cloud Data Flow could benefit from a better user interface and stronger community support. Enhancing documentation clarity and expanding support for more languages and tools would be beneficial.

Ease of Deployment and Customer Service: Teradata is primarily deployed on-premises but offers cloud options with robust support, though response times could see improvement. Spring Cloud Data Flow offers hybrid deployment flexibility and is known for strong customer service. Both offer reliable technical support, with Teradata receiving positive feedback for its extensive services through Teradata University.

Pricing and ROI: Teradata is recognized for high performance at a premium price, delivering significant ROI through improved analytics and system speed. Recent pricing models are becoming more flexible but may still be prohibitive for smaller projects. Spring Cloud Data Flow, as an open-source solution, reduces initial investment costs, offering value through its free-to-use model. Teradata justifies its price with powerful features, while Spring Cloud Data Flow provides a cost-effective solution for data stream management.

To learn more, read our detailed Spring Cloud Data Flow vs. Teradata Report (Updated: September 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 (10th)

Teradata

Ranking in Data Integration

17th

Average Rating

8.2

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

Customer Experience Management (6th), Backup and Recovery (21st), Relational Databases Tools (8th), Data Warehouse (3rd), BI (Business Intelligence) Tools (13th), Marketing Management (5th), Cloud Data Warehouse (4th)

Mindshare comparison

As of October 2025, in the Data Integration category, the mindshare of Spring Cloud Data Flow is 1.2%, up from 1.0% compared to the previous year. The mindshare of Teradata is 0.8%, up from 0.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration Market Share Distribution
Product	Market Share (%)
Teradata	0.8%
Spring Cloud Data Flow	1.2%
Other	98.0%

Data Integration

Featured Reviews

Kaleeswaran Karuppusamy

Cloud Application Architect at Lumen Technologies

Helps retrieve data and with data processing but is not so easy to use

There are no stability issues in the tool. Compared to Apache Sling, Spring Cloud Data Flow is not easy to use. People prefer Apache Sling when dealing with their use cases. I don't know whether Spring Cloud Data Flow will be demanded a lot in the market because there are a lot of other options available, especially open-source tools like Apache Sling, which is getting a lot of attention from people. A lot of people have started using Apache Sling, so I don't know how much more visible Spring Cloud Data Flow will be in the future.

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Kirk Robinson

Interim and Fractional CIO and CTO at a consultancy with 11-50 employees

Has improved data quality, optimized reporting processes, and enabled predictive insights across business units

The limitation we encountered was related to speed, prompting us to increase our AWS cloud thresholds and benchmarks on the servers, adding more throughput. We have been testing that, but speed remains one of our key issues. The integration has been awesome because of the platforms and their usage, and usability is great. The most challenging aspect is finding Teradata resources, so we are focusing on internal training and looking for more Teradata experts. If Teradata could provide a list of certified experts, that would be fantastic. I rated Teradata a nine because the main area for improvement is the bandwidth of resources that could assist us in applying to our projects, specifically more certified and expert resources. The market share of Teradata professionals is limited, creating an issue for us.

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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

"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."

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

"The product is very user-friendly."

"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 dashboards in Spring Cloud Dataflow are quite valuable."

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

"In Data Lab, you can schedule any testing you want to do in production. You can take a small subset of data from production, copy it there, and run all your tests. It reduces your testing costs because it's all in the lab."

"The solution's banking model, called FSLDM (Financial Services Logical Data Model), is sophisticated and good."

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

"The most valuable feature of Teradata is security. It runs on Unix and Linux platforms which provide better security."

"The most valuable feature is the ease of running queries."

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

"The data processing, clustering, and distributed computing are impressive."

"The solution scales well on the cloud."

More Teradata pros

Cons

"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 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."

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

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

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

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

"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."

"The solution is stable. However, there are times when we are using large amounts of data and we can see some latency issues."

"When backups are performed, it locks the database, preventing user access, which is a concern."

"Since I was working on the very basic, legacy systems, the memory thing was always a challenge. If Teradata is moving to the cloud, the space constraint or the memory issue that my company generally faces will eventually resolve, in time. What I'd like to see in the next release of Teradata is that it becomes full-fledged on the cloud, apart from better connectivity to various systems. For example, if I have to read or include a Python script, if I write some basic codes, I should be able to read even unstructured data. I know that it's not supported even in Snowflake, but at least semi-structured data support, if that can be a little more enhanced, that would be good."

"The user interface needs to be improved."

"Teradata is a bit late for the cloud."

"Teradata's UI could be improved."

"Stability-wise, we have had some issues with automation and the ability to handle large datasets."

"I'm not sure about the unstructured data management capabilities. It could be improved."

More Teradata cons

Pricing and Cost Advice

"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 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."

"We are looking for a more flexible cost model for the next version that we use, whether it be cloud or on-premise."

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

"It is still a very expensive solution. While I very much like the pure technological supremacy of the software itself, I believe Teradata as a company needs to become more affordable. They are already losing the market to more flexible or cheaper competitors."

"It's a very expensive product."

"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."

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

"The product cost is high for what the client gets. There may be more cost-effective solutions for small and medium-sized organizations."

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

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

24%

Computer Software Company

14%

Retailer

Manufacturing Company

Financial Services Firm

25%

Computer Software Company

Manufacturing Company

Healthcare Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

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

By reviewers
Company Size	Count
Small Business	26
Midsize Enterprise	12
Large Enterprise	49

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, Teradata Vantage Enterprise (DIY)

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.

Broadcom

Teradata is a powerful tool for handling substantial data volumes with its parallel processing architecture, supporting both cloud and on-premise environments efficiently. It offers impressive capabilities for fast query processing, data integration, and real-time reporting, making it suitable for diverse industrial applications.

Known for its robust parallel processing capabilities, Teradata effectively manages large datasets and provides adaptable deployment across cloud and on-premise setups. It enhances performance and scalability with features like advanced query tuning, workload management, and strong security. Users appreciate its ease of use and automation features which support real-time data reporting. The optimizer and intelligent partitioning help improve query speed and efficiency, while multi-temperature data management optimizes data handling.

What are the key features of Teradata?

Parallel Processing Architecture: Enables efficient handling of substantial data volumes.
Cloud and On-Premise Deployment: Offers seamless adaptability across environments.
Query Tuning: Improves speed and performance of data retrieval processes.
Workload Management: Ensures optimal resource allocation for enhanced performance.
Robust Security: Provides high levels of data protection and system integrity.
Data Integration: Facilitates cohesive data management from multiple sources.
Automation for Real-time Reporting: Enhances timely data insights and decision-making.
Optimizer and Intelligent Partitioning: Further increase query speed and system efficiency.
Multi-Temperature Data Management: Optimizes the handling and retrieval of data.

What benefits and ROI do users look for?

Efficient Data Management: Facilitates smooth integration and processing of diverse data sets.
Scalability: Easy adjustment to increasing or decreasing data requirements.
Improved Performance: Fast query speeds and optimized resource use.
Comprehensive Security: Safeguards data integrity and accessibility.
Ease of Use: Simplifies data handling and operational processes.

In the finance, retail, and government sectors, Teradata is employed for data warehousing, business intelligence, and analytical processing. It handles vast datasets for activities like customer behavior modeling and enterprise data integration. Supporting efficient reporting and analytics, Teradata enhances data storage and processing, whether deployed on-premise or on cloud platforms.

Sample Customers

Information Not Available

Netflix

Spring Cloud Data Flow vs. Teradata