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.

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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.

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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

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

"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."

"Things have started moving faster in my company, such as data retrieval happens more quickly."

"The solution scales well on the cloud."

"It's a pre-configured appliance that requires very little in terms of setting-up."

"Teradata can be easily used in ETL mode transformations, so there is no need for expensive and inconvenient ETL tools"

"BTEQ is the best feature of Teradata, as it allows me to execute multiple queries such as select, insert, update, and delete in a single script, handle errors, automate running multiple SQL statements, and schedule ETL jobs, making it lightweight and scriptable, unlike SQL Assistant."

"A conventional and easily defined way to build a data warehouse or a layer of data marts."

"Teradata's most valuable feature is that it's easy to use."

"The feature that we find most valuable is its ability to perform Massive Parallel Processing."

More Teradata pros

Cons

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

"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."

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

"Azure Synapse SQL has evolved from a solely dedicated support tool to a data lake. It can store data from multiple systems, not just traditional database management systems. On the other hand, Teradata has limitations in loading flat files or unstructured data directly into its warehouse. In Azure Synapse SQL, we can implement machine learning using Python scripts. Additionally, Azure Synapse SQL offers advanced analytical capabilities compared to Teradata. Teradata is also expensive."

"Their level of technical support is adequate. It could be better."

"Limited interest and success in some areas make us hesitate about upgrading."

"The following could be better: licensing, architecture openness, integration with other tools."

"Teradata is a bit late for the cloud."

"Teradata needs to pay attention to the cloud-based solution to make sure it runs smoothly."

"They should add more connectors to different platforms."

More Teradata cons

Pricing and Cost Advice

Information not available

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

"In the past, it turned out that other solutions, in order to provide the full range of abilities that the Teradata platform provides plus the migration costs, would end up costing more than Teradata does."

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

"The price of Teradata could be less expensive."

"Teradata is currently making improvements in this area."

"The cost is significantly high."

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

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

More Teradata pricing and cost advice

See which vendors are best for you

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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,...

PlanetScale vs Amazon Aurora Serverless

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Compared 18% of the time

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Compared 10% of the time

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Compared 8% of the time

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Compared 5% of the time

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Compared 5% of the time

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Compared 5% of the time

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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