Amazon Aurora Serverless vs Teradata comparison

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Amazon Aurora Serverless

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Executive SummaryUpdated on Apr 20, 2025

Teradata and Amazon Aurora Serverless compete in the database management systems category. Amazon Aurora Serverless often has an edge with its scalability and cost-effectiveness, appealing to developers with its ability to efficiently manage variable workloads.

Features: Teradata offers advanced analytics, support for large-scale operations, and robust data management tools. Amazon Aurora Serverless features automatic scaling, full MySQL and PostgreSQL compatibility, and high availability. Aurora's flexibility and modern architecture are particularly beneficial in environments that demand adaptive resources and cost management.

Ease of Deployment and Customer Service: Teradata requires a more complex setup suited for large bespoke data environments with dedicated IT resources. Amazon Aurora Serverless simplifies deployment through its serverless model, reducing time to market and administrative efforts. Both products support strong customer service, but Aurora's straightforward setup offers an advantage for developers looking for quick system integration.

Pricing and ROI: Teradata involves significant upfront costs with strong ROI for deep analytics insight capabilities. Amazon Aurora Serverless offers a cost-efficient, pay-as-you-go model attracting startups and enterprises with limited budgets while supporting growth. Aurora's flexible pricing often results in favorable ROI for rapidly scaling operations.

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

Amazon Aurora Serverless vs. Teradata

April 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

20th

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

7th

Average Rating

8.2

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

Customer Experience Management (6th), Backup and Recovery (20th), Data Integration (17th), Data Warehouse (3rd), BI (Business Intelligence) Tools (10th), Marketing Management (6th), Cloud Data Warehouse (6th)

Mindshare comparison

As of April 2025, in the Relational Databases Tools category, the mindshare of Amazon Aurora Serverless is 0.2%. The mindshare of Teradata is 5.5%, up from 5.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Relational Databases Tools

Featured Reviews

Anibal Palacios

CTO at a consultancy with 11-50 employees

Database availability has improved with quick recovery and enhanced network setup

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 Aurora is used as it is an easier solution for our requirements and offers high availability. It allows us to…

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SurjitChoudhury

Data engineer at Cocos pt

Offers seamless integration capabilities and performance optimization features, including extensive indexing and advanced tuning capabilities

We created and constructed the warehouse. We used multiple loading processes like MultiLoad, FastLoad, and Teradata Pump. But those are loading processes, and Teradata is a powerful tool because if we consider older technologies, its architecture with nodes, virtual processes, and nodes is a unique concept. Later, other technologies like Informatica also adopted the concept of nodes from Informatica PowerCenter version 7.x. Previously, it was a client-server architecture, but later, it changed to the nodes concept. Like, we can have the database available 24/7, 365 days. If one node fails, other nodes can take care of it. Informatica adopted all those concepts when it changed its architecture. Even Oracle databases have since adapted their architecture to them. However, this particular Teradata company initially started with its own different type of architecture, which major companies later adopted. It has grown now, but initially, whatever query we sent it would be mapped into a particular component. After that, it goes to the virtual processor and down to the disk, where the actual physical data is loaded. So, in between, there's a map, which acts like a data dictionary. It also holds information about each piece of data, where it's loaded, and on which particular virtual processor or node the data resides. Because Teradata comes with a four-node architecture, or however many nodes we choose, the cost is determined by that initially. So, what type of data does each and every node hold? It's a shared-no architecture. So, whatever task is given to a virtual processor it will be processed. If there's a failure, then it will be taken care of by another virtual processor. Moreover, this solution has impacted the query time and data performance. In Teradata, there's a lot of joining, partitioning, and indexing of records. There are primary and secondary indexes, hash indexing, and other indexing processes. To improve query performance, we first analyze the query and tune it. If a join needs a secondary index, which plays a major role in filtering records, we might reconstruct that particular table with the secondary index. This tuning involves partitioning and indexing. We use these tools and technologies to fine-tune performance. When it comes to integration, tools like Informatica seamlessly connect with Teradata. We ensure the Teradata database is configured correctly in Informatica, including the proper hostname and properties for the load process. We didn't find any major complexity or issues with integration. But, these technologies are quite old now. With newer big data technologies, we've worked with a four-layer architecture, pulling data from Hadoop Lake to Teradata. We configure Teradata with the appropriate hostname and credentials, and use BTEQ queries to load data. Previously, we converted the data warehouse to a CLD model as per Teradata's standardized procedures, moving from an ETL to an EMT process. This allowed us to perform gap analysis on missing entities based on the model and retrieve them from the source system again. We found Teradata integration straightforward and compatible with other tools.

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

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

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

"The ease of deployment is useful so clients are up and running quickly in comparison to other products."

"It has increased the speed of reporting."

"Parallel processing features have helped to easily dump any size of data and retrieve data with great performance."

"It's very, very fast"

"The most valuable feature is the ease of uploading data from multiple sources."

"The tool's most valuable feature is the warehousing model."

"It effectively has allowed us to remove over 20 portion copies of the data sets on other DB platforms for real-time operational reporting purposes."

"The most valuable feature of Teradata is the quick processing of large data."

More Teradata pros

Cons

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

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

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

"The primary challenge with Teradata lies in its cost structure, encompassing subscription fees, software licenses, and hardware expenses."

"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."

"GUI of administrative tools is really outdated."

"The increasing volumes of data demand more and more performance."

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

"Teradata can improve the way it handles big data and unstructured data."

"I would like to see more integration with many different types of data."

"There is some improvement required on OLTP level and some analytical function is missing."

More Teradata cons

Pricing and Cost Advice

Information not available

"I rate the product price a nine on a scale of one to ten, where one is cheap and ten is expensive."

"The cost is significantly high."

"The price of Teradata is expensive. However, what they deliver they are outstanding. If you're looking for an inexpensive solution to run a database, this isn't your tool. It's the Ferrari of databases for data warehousing."

"Teradata is not cheap, but you get what you pay for."

"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."

"We had a lot of parties involved when purchasing from the AWS Marketplace. They are very flexible and aggressive in trying to close the deal. They are good at what they have to offer and listening to the customer. It's a two-way street."

"The price needs to be more competitive as Hadoop, Redshift, Snowflake, etc are constantly making way into EDW space."

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

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

No data available

Financial Services Firm

26%

Computer Software Company

11%

Healthcare Company

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

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,...

Oracle Exadata vs Teradata

Comparisons

No data available

Compared 13% of the time

SQL Server vs Teradata

Compared 10% of the time

MySQL vs Teradata

Compared 7% of the time

Snowflake vs Teradata

Compared 7% of the time

IBM Db2 Database vs Teradata

Compared 6% of the time

More Teradata Competitors

Product Reports

Relational Databases Tools

March 2025

Download Amazon Aurora Serverless product report

Download Teradata product report

April 2025

Also Known As

No data available

IntelliFlex, Aster Data Map Reduce, , QueryGrid, Customer Interaction Manager, Digital Marketing Center, Data Mover, Data Stream Architecture

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 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