Amazon Aurora Serverless vs Teradata comparison

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Amazon Aurora Serverless

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Executive SummaryUpdated on Jan 4, 2026

Teradata and Amazon Aurora Serverless are competing database solutions with Teradata known for robust data warehousing capabilities, while Amazon Aurora Serverless is favored for its scalability and cost efficiency. Amazon Aurora Serverless's advanced features give it an upper hand for businesses focusing on modern cloud-native applications.

Features: Teradata offers high-performance analytics, scalability for large datasets, and comprehensive integration with enterprise systems. Amazon Aurora Serverless provides automated scaling, high availability, and fault tolerance.

Ease of Deployment and Customer Service: Teradata provides extensive deployment options with strong customer support, suiting large enterprises needing tailored solutions. Amazon Aurora Serverless offers straightforward deployment in a managed environment, simplifying setup and reducing operational overhead.

Pricing and ROI: Teradata incurs higher setup costs but offers a strong ROI through deep analytics for large enterprises. Amazon Aurora Serverless provides a flexible, pay-as-you-go model without upfront costs, making it cost-effective for organizations needing elastic scalability and quick ROI.

To learn more, read our detailed Amazon Aurora Serverless vs. Teradata Report (Updated: December 2025).

Amazon Aurora Serverless vs. Teradata

December 2025

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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

Amazon Aurora Serverless

Ranking in Relational Databases Tools

22nd

Average Rating

9.0

Reviews Sentiment

8.8

Number of Reviews

Ranking in other categories

No ranking in other categories

Teradata

Ranking in Relational Databases Tools

6th

Average Rating

8.2

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

Customer Experience Management (6th), Backup and Recovery (15th), Data Integration (15th), Data Warehouse (3rd), BI (Business Intelligence) Tools (8th), Marketing Management (5th), Cloud Data Warehouse (3rd), Database Management Systems (DBMS) (3rd)

Mindshare comparison

As of January 2026, in the Relational Databases Tools category, the mindshare of Amazon Aurora Serverless is 1.2%, up from 0.1% compared to the previous year. The mindshare of Teradata is 4.0%, down from 5.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Relational Databases Tools Market Share Distribution
Product	Market Share (%)
Teradata	4.0%
Amazon Aurora Serverless	1.2%
Other	94.8%

Relational Databases Tools

Featured Reviews

MohitGupta3

Cloud Infrastructure Architect - AWS at Infopro Digital

Seamless growth management through serverless efficiency and reasonable pricing

The most valuable feature of Amazon Aurora Serverless is its serverless nature, which means I do not have to maintain the underlying infrastructure. Additionally, it is highly scalable, and its pricing model is favorable. Aurora's automatic scaling greatly enhances our operational efficiency by eliminating the need to set specific thresholds and preventing client data access issues due to uneven growth. Its serverless setup allows us to manage costs effectively. Other notable features include direct integration with tools like SFTP Go for media file uploads, automatic backups ensuring data recovery, and its scalability in terms of handling growing database demands.

Read full review

David Durand Velásquez

Engineers at a consultancy with 11-50 employees

Delivers consistent performance and enables advanced analytics across complex data environments

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.

Read full review

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros

"Aurora could improve its affordability, even though its price is very completive compared to DBs as SLQ Server."

"The most valuable feature of Amazon Aurora Serverless is its serverless nature, which means I do not have to maintain the underlying infrastructure."

"Amazon Aurora Serverless is easy to scale, offering a cluster-based shared scaling model with options for Autoscale."

"There are several features of Teradata that I like. One of the most basic is the indexes. I also like that it provides lower TCO. It also has the optimizer feature which is a good feature and isn't found in other legacy systems. Parallelism is also another feature I like in Teradata because when you are running or hosting on multiple systems, you have this shared-nothing architecture that helps. Loading and unloading in Teradata are also really helpful compared to other systems."

"Their extensive experience in data warehousing, the platform's performance, and their strong reputation in the market are the most valuable."

"It's very, very fast"

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

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

"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."

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

"I found all parts --loading, transformation, processing & querying work in parallel, and end-to-end-- to be valuable."

More Teradata pros

Cons

"Aurora could improve its affordability, as it is currently considered a bit expensive."

"Amazon Aurora could improve its detailed monitoring, especially in CloudWatch, to provide more precise query level insights."

"Amazon Aurora Serverless could benefit from a few more security features, particularly in terms of its accessibility."

"The initial setup was complex as we had to rewrite a lot of the code."

"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."

"It's primarily designed for big projects and therefore, the pricing is pretty high. It's not suitable for smaller companies."

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

"There are some ways that the handling of unstructured data could be improved."

"The setup is not straightforward."

"It could be a bit more user-friendly."

"Needs compatibility with more Big Data platforms."

More Teradata cons

Pricing and Cost Advice

Information not available

"I would advise others to look into migration and setup as a fixed price and incorporate a SaaS option for other Teradata services."

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

"Teradata is expensive, so it's typically marketed to big customers. However, there have been some changes, and Teradata is now offering more flexible pricing models and equipment leasing. They've added pay-as-you-go and cloud models, so it's changing, but Teradata is generally known as an expensive high-end product."

"The initial cost may seem high, but the TCO is low."

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

"Make sure you have the in-house skills to design and support the solution, as relying on external sources is extremely costly and tends to lock you into specific platforms, tools, and paradigms."

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

"The solution requires a license."

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…

Read full review

Top Industries

By visitors reading reviews

No data available

Financial Services Firm

24%

Manufacturing Company

Computer Software Company

Government

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

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

Questions from the Community

What is your experience regarding pricing and costs for Amazon Aurora Serverless?

In my experience, Aurora is a bit expensive. The costs depend on the size of the database.

What needs improvement with Amazon Aurora Serverless?

Aurora could improve its affordability, as it is currently considered a bit expensive. There is room to make it more cost-effective for users even though its price is very completive compared to DB...

What is your primary use case for Amazon Aurora Serverless?

I use Aurora mainly for creating and maintaining databases, such as Aurora (MySQL version) databases, within the system. I value it for its network security and quicker recovery options.

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

Relational Databases Tools

January 2026

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January 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

Amazon Aurora Serverless is a flexible, on-demand database service that automatically scales based on application needs. It removes the need for database management, allowing businesses to focus on innovation and efficiency.

This database service provides automatic rescaling of compute capacity, which makes it uniquely suited to unpredictable workloads and applications with variable demand. It integrates seamlessly with existing AWS services and supports both MySQL and PostgreSQL, ensuring high availability and durability while reducing costs associated with over-provisioning of resources. Aurora Serverless dynamically adjusts capacity, providing a cost-effective and reliable solution for cloud-native applications and serverless architectures.

What are the key features of Amazon Aurora Serverless?

Automatic Scaling: Instantly adjusts capacity in response to demand.
Managed Infrastructure: Offloads database maintenance and management tasks.
High Availability: Provides multi-AZ support to ensure uptime and reliability.
MySQL and PostgreSQL Compatibility: Supports migrations and existing applications.
Pay-Per-Use: Charges are based on the exact resources utilized.

What benefits can be found in reviews of Amazon Aurora Serverless?

Cost Savings: Helps significantly reduce infrastructure expenses.
Operational Efficiency: Frees up time for the IT team for strategic projects.
Scalability: Easily accommodates fluctuating application demands.
Integration: Works seamlessly with AWS services, enhancing service reach.
Resiliency: Robust data protection features contribute to data security.

Amazon Aurora Serverless has been widely adopted across industries such as ecommerce and online media, where demand can vary greatly and unpredictably. For instance, ecommerce platforms benefit from auto-scaling during peak shopping seasons, ensuring uninterrupted service without incurring unnecessary costs during off-peak periods. Similarly, media companies leverage its auto-scaling capabilities to manage traffic spikes during events or breaking news.

Amazon Web Services (AWS)

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