Apache Kafka on Confluent Cloud vs Teradata comparison

Apache Kafka on Confluent C...

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Executive Summary

We performed a comparison between Apache Kafka on Confluent Cloud and Teradata based on real PeerSpot user reviews.

Find out what your peers are saying about Databricks, Amazon Web Services (AWS), Apache and others in Streaming Analytics.

To learn more, read our detailed Streaming Analytics Report (Updated: March 2026).

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Streaming Analytics

March 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:

ROI

Sentiment score

4.7

Confluent Cloud's Kafka offers cost-effective scalability and reliability, enhancing data processing and schema management despite higher costs.

Sentiment score

6.9

Teradata significantly boosts speed, efficiency, and ROI, with studies showing a 427% average ROI over three years.

Returns depend on the application you deploy and the amount of benefits you are getting, which depends on how many applications you are deploying, what are the sorts of applications, and what are the requirements.

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Chief Architect at a financial services firm with 10,001+ employees

At least fifteen to twenty percent of our time has been saved using Teradata, which has positively affected team productivity and business outcomes.

Shugoyal Shugoyal

Senior product analyst at a financial services firm with 10,001+ employees

Independent research showed that Teradata VantageCloud users achieved an average ROI of 427% across three years with payback under a year, demonstrating the platform's ability to deliver a strong financial return.

Engineers at a consultancy with 11-50 employees

We have realized a return on investment, with a reduction of staff from 27 to eight, and our current return on investment is approximately 14%.

For more quotes and insights, download the Teradata report

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

Customer Service

Sentiment score

6.8

Apache Kafka support on Confluent Cloud is praised for timely and competent assistance, with high user satisfaction ratings.

Sentiment score

7.1

Teradata's support is praised for professionalism and responsiveness, but feedback on speed is mixed; training resources enhance service.

I was getting prompt responses, and it was nicely handled regarding the support.

Lead Software Engineer at a tech vendor with 10,001+ employees

I would rate them eight if 10 was the best and one was the worst.

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Chief Architect at a financial services firm with 10,001+ employees

The customer support for Teradata has been great.

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

They are responsive and knowledgeable, and the documentation is very helpful.

Engineers at a consultancy with 11-50 employees

Customer support is very good, rated eight out of ten under our essential agreement.

For more quotes and insights, download the Teradata report

Team Leader for Data Base Administrators at a government with 1,001-5,000 employees

Scalability Issues

Sentiment score

5.8

Apache Kafka on Confluent Cloud is scalable and flexible, though some users report reliability issues when scaling.

Sentiment score

7.5

Teradata offers scalable cloud and on-premise solutions with strong adaptability, overcoming hardware limitations and cost challenges efficiently.

According to me, it is quite scalable in terms of all the data it can handle and stream.

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Lead Software Engineer at a tech vendor with 10,001+ employees

Whenever we need more resources, we can add that in Teradata, and when not needed, we can scale it down as well.

Shugoyal Shugoyal

Senior product analyst at a financial services firm with 10,001+ employees

This flexibility allows organizations to scale according to their needs, balancing performance, cost, and compliance requirements.

For more quotes and insights, download the Teradata report

Engineers at a consultancy with 11-50 employees

This expansion can occur without incurring downtime or taking systems offline.

RajeshKumar25

Principal Consultant & Director at Quensulting

Stability Issues

Sentiment score

6.0

Apache Kafka on Confluent Cloud is stable and reliable, with occasional issues in high traffic and dashboard access.

Sentiment score

8.3

Teradata's robust architecture ensures exceptional stability and reliability, with minimal downtime and high user ratings despite some integration challenges.

No quotes available

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Its massively parallel process architecture allows the platform to distribute workload efficiently, enabling organizations to run heavy analytic queries without compromising speed or stability.

Engineers at a consultancy with 11-50 employees

I find the stability to be almost a ten out of ten.

For more quotes and insights, download the Teradata report

Team Leader for Data Base Administrators at a government with 1,001-5,000 employees

The workload management and software maturity provide a reliable system.

RajeshKumar25

Principal Consultant & Director at Quensulting

Room For Improvement

Apache Kafka on Confluent Cloud needs improvements in integrations, user interface, cost, monitoring, and configuration for enhanced functionality.

Teradata requires improvements in transaction processing, scalability, UI, cost-effectiveness, analytics features, integration capabilities, and security measures.

If it were easier to configure clusters and had more straightforward configuration, high-level API abstraction in the APIs could improve it.

FABIO LUIS VELLOSO DA SILVA

Partner at SouJava

Regarding additional improvements, I would say probably around error handling, where when we encounter errors specific to our response structures and everything, or the tables or anything of that nature, it would be better if we were prompted with better error handling mechanisms.

Lead Software Engineer at a tech vendor with 10,001+ employees

Observability and monitoring are areas that could be enhanced.

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Chief Architect at a financial services firm with 10,001+ employees

I want to highlight two features for improvement: first, storing data in various formats without requiring a tabular structure, accommodating unstructured data; and second, adding AI ML features to better integrate Gen AI, LLM concepts, and user-friendly experiences such as text-to-SQL capabilities.

Ganesh Verma

Data Engineer at Tredence Inc.

Unlike SQL and Oracle, which have in-built replication capabilities, we don't have similar functionality with Teradata.

Team Leader for Data Base Administrators at a government with 1,001-5,000 employees

The most challenging aspect is finding Teradata resources, so we are focusing on internal training and looking for more Teradata experts.

For more quotes and insights, download the Teradata report

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

Setup Cost

Enterprise users of Apache Kafka on Confluent Cloud find pricing accessible but warn of potential cost surges with added features.

Teradata offers high-value analytics with flexible pricing, excelling in performance and ROI, ideal for large enterprises and data-intensive sectors.

I thought Confluent would stop me when I crossed the credits, but it did not, and then I got charged.

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Lead Software Engineer at a tech vendor with 10,001+ employees

Teradata is much more expensive than SQL, which is well-performed and cheaper.

Team Leader for Data Base Administrators at a government with 1,001-5,000 employees

Initially, it may seem expensive compared to similar cloud databases, however, it offers significant value in performance, stability, and overall output once in use.

RajeshKumar25

Principal Consultant & Director at Quensulting

Role-based access control (RBAC), strong audit and compliance features, high availability, fault tolerance, and encrypted data at rest and in-transit are key features.

For more quotes and insights, download the Teradata report

Engineers at a consultancy with 11-50 employees

Valuable Features

Apache Kafka on Confluent Cloud enables scalable, efficient real-time data processing with seamless platform integration and advanced management features.

Teradata excels in parallel processing, scalability, and performance, offering robust data management, security, and integration for efficient data warehousing.

These features are important due to scalability and resiliency.

FABIO LUIS VELLOSO DA SILVA

Chief Architect at a financial services firm with 10,001+ employees

The Kafka Streams API helps with real-time data transformations and aggregations.

Partner at SouJava

The best features Apache Kafka on Confluent Cloud offers would be the connection with various external systems through various languages such as Python and C#.

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Lead Software Engineer at a tech vendor with 10,001+ employees

Teradata's security helps our organization meet compliance requirements such as GDPR and IFRS, and it is particularly essential for revenue contracting or revenue recognition.

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

Its architecture allows information to be processed efficiently while maintaining stable performance, even in highly demanding environments.

For more quotes and insights, download the Teradata report

Engineers at a consultancy with 11-50 employees

It facilitates data integration, where we integrate and analyze data from various sources, making it a powerful and high-quality reliable solution for the company.

reviewer2783274

Senior Data Engineer at a media company with 1,001-5,000 employees

Categories and Ranking

Apache Kafka on Confluent C...

Average Rating

8.6

Reviews Sentiment

5.6

Number of Reviews

Ranking in other categories

Streaming Analytics (11th)

Teradata

Average Rating

8.2

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

Customer Experience Management (6th), Backup and Recovery (13th), Data Integration (11th), Relational Databases Tools (5th), Data Warehouse (3rd), BI (Business Intelligence) Tools (7th), Marketing Management (5th), Cloud Data Warehouse (2nd), Database Management Systems (DBMS) (5th)

Mindshare comparison

Apache Kafka on Confluent Cloud and Teradata aren’t in the same category and serve different purposes. Apache Kafka on Confluent Cloud is designed for Streaming Analytics and holds a mindshare of 0.6%.
Teradata, on the other hand, focuses on Data Warehouse, holds 8.8% mindshare, down 15.7% since last year.

Streaming Analytics Mindshare Distribution
Product	Mindshare (%)
Apache Kafka on Confluent Cloud	0.6%
Apache Flink	9.8%
Databricks	8.2%
Other	81.4%

Streaming Analytics

Data Warehouse Mindshare Distribution
Product	Mindshare (%)
Teradata	8.8%
Snowflake	9.5%
Oracle Exadata	7.6%
Other	74.1%

Data Warehouse

Featured Reviews

Has unified log streams from multiple systems and accelerated issue tracking through streamlined setup

Lead Software Engineer at a tech vendor with 10,001+ employees

I think Apache Kafka on Confluent Cloud can be improved by probably working more around Confluent or the tool. In my opinion, it should utilize the response structures in a better way or be able to detect if there is any variable or if there is any data structure that is mismatched, as it would be easier than us manually having to put in the exact name in order for it to match the response. Regarding additional improvements, I would say probably around error handling, where when we encounter errors specific to our response structures and everything, or the tables or anything of that nature, it would be better if we were prompted with better error handling mechanisms. I do not think there are any other improvements Apache Kafka on Confluent Cloud needs, aside from error handling and response structures.

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Delivers consistent performance and enables advanced analytics across complex data environments

Engineers at a consultancy with 11-50 employees

Teradata stands out as a solid platform for managing and analyzing large volumes of data. Its architecture allows information to be processed efficiently while maintaining stable performance, even in highly demanding environments. One of its most notable strengths is the ability to run complex queries at high speed, which is essential for organizations that require timely and reliable analytics. Teradata offers a well-integrated ecosystem that supports working with different types of data and enables scalability as organizational needs grow. Its focus on advanced analytics, integration with modern business intelligence tools, and the ability to operate both on-premise and in the cloud make it a versatile solution for data warehousing and large-scale processing. Teradata's stability, technological maturity, and the availability of strong documentation and best practices are noteworthy. I consider Teradata to be a tool with great potential for any organization looking to enhance its analytical capabilities, optimize data processing, and move toward more data-driven decision-making. Teradata stands out as a solid platform for managing a large volume of data in different projects. Its architecture allows information to be processed efficiently while maintaining stable performance, even in high-demanding environments. A well-integrated AI ecosystem that supports working with different types of data and enables scalability as organizational needs grow across different kinds of enterprises or organizations. The focus on advanced analytics integration with modern business intelligence tools is particularly valuable. Teradata combines a powerful parallel process and optimizing SQL engine with a highly scalable architecture allowing businesses to execute complex queries and analytics in real-time. It supports multi-cloud, hybrid, and on-premise environments, giving organizations flexibility to choose the setup that best aligns with their strategy. One of the biggest strengths is the ability to unify disparate data sources and support high concurrency, enabling different teams, such as analytics, operations, BI, and data science, to access consistent, trusted data across the enterprise.

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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…

Read full review

Top Industries

By visitors reading reviews

Construction Company

16%

Financial Services Firm

13%

Manufacturing Company

Comms Service Provider

Financial Services Firm

20%

Manufacturing Company

Construction Company

Comms Service Provider

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	6
Midsize Enterprise	3
Large Enterprise	8

By reviewers
Company Size	Count
Small Business	28
Midsize Enterprise	13
Large Enterprise	52

Questions from the Community

What needs improvement with Apache Kafka on Confluent Cloud?

What is your primary use case for Apache Kafka on Confluent Cloud?

I have used Apache Kafka on Confluent Cloud for one of my projects with regard to log monitoring. My main use case for Apache Kafka on Confluent Cloud in that project was mainly streaming of the lo...

What advice do you have for others considering Apache Kafka on Confluent Cloud?

My advice to others looking into using Apache Kafka on Confluent Cloud is that it is easier and has a low learning curve. If there is any use case regarding streaming, I would suggest starting off ...

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,...

n8n vs Apache Kafka on Confluent Cloud

Comparisons

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WarpStream vs Apache Kafka on Confluent Cloud

Compared 19% of the time

Tecton Feature Store vs Apache Kafka on Confluent Cloud

Compared 10% of the time

Cloud Security Connector for Zscaler vs Apache Kafka on Confluent Cloud

Compared 9% of the time

Nomad Media vs Apache Kafka on Confluent Cloud

Compared 9% of the time

More Apache Kafka on Confluent Cloud Competitors

Snowflake vs Teradata

Compared 4% of the time

Oracle Database vs Teradata

Compared 4% of the time

SQL Server vs Teradata

Compared 4% of the time

Oracle Exadata vs Teradata

Compared 3% of the time

IBM Db2 Database vs Teradata

Compared 2% of the time

More Teradata Competitors

Product Reports

Buyer's Guide

Apache Kafka on Confluent Cloud

April 2026

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Buyer's Guide

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April 2026

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

Apache Kafka on Confluent Cloud provides real-time data streaming with seamless integration, enhanced scalability, and efficient data processing, recognized for its real-time architecture, ease of use, and reliable multi-cloud operations while effectively managing large data volumes.

Apache Kafka on Confluent Cloud is designed to handle large-scale data operations across different cloud environments. It supports real-time data streaming, crucial for applications in transaction processing, change data capture, microservices, and enterprise data movement. Users benefit from features like schema registry and error handling, which ensure efficient and reliable operations. While the platform offers extensive connector support and reduced maintenance, there are areas requiring improvement, including better data analysis features, PyTRAN CDC integration, and cost-effective access to premium connectors. Migrating with Kubernetes and managing message states are areas for development as well. Despite these challenges, it remains a robust option for organizations seeking to distribute data effectively for analytics and real-time systems across industries like retail and finance.

What are the key features of Apache Kafka on Confluent Cloud?

Seamless Integration: Connects with many data sources seamlessly.
Enhanced Scalability: Easily scales to manage increasing data loads.
Schema Registry: Maintains compatibility and evolution of schemas.
Offset Management: Tracks consumer progress efficiently.
Error Handling: Offers mechanisms to manage inaccuracies effectively.
Connector Support: Extensive connectors for diverse third-party tools.

What benefits should users seek in reviews?

Reliability: Consistent performance in multi-cloud environments.
Ease of Use: Simplified operations and maintenance.
Developer Efficiency: Streamlined features that save developers time.
Data Volume Handling: Capable of managing large-scale data streaming.

In industries like retail and finance, Apache Kafka on Confluent Cloud is implemented to manage real-time location tracking, event-driven systems, and enterprise-level data distribution. It aids in operations that require robust data streaming, such as CDC, log processing, and analytics data distribution, providing a significant edge in data management and operational efficiency.

Confluent

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.