Amazon Aurora vs Teradata comparison

Read 76 Teradata reviews

4,989 Views
3,803 Comparison Views

87% willing to recommend

Amazon Aurora

Comparison Buyer's Guide

Download the report

Executive SummaryUpdated on Jan 12, 2025

Teradata and Amazon Aurora compete in the database management and analytics category. Based on the comparison, Aurora seems to have the upper hand in cloud environments due to its integration with AWS services and scalability.

Features: Teradata is known for its massively parallel processing capabilities, adaptability, and workload management, making it suitable for large-scale data operations. It also highlights its optimizer, scalability, and security features. Amazon Aurora impresses with superior speed, high availability, and seamless integration with AWS services, making it highly efficient for cloud environments.

Room for Improvement: Teradata faces cost challenges, limited functionality for unstructured data, and needs better cloud integration. Enhancements in SQL functionalities and cloud compatibility are also desired. Amazon Aurora requires improvements in pricing, AI features, and deeper performance insights. Its cost and dependency on AWS are concerns when considering broader integration.

Ease of Deployment and Customer Service: Teradata offers diverse deployment options, including on-premises, hybrid, and cloud, though users report complexity in setup and scaling. Aurora primarily deploys in public and private cloud environments, simplifying processes for AWS users. Both receive positive customer service feedback, with Teradata's technical support and Aurora's AWS support infrastructure being noted.

Pricing and ROI: Teradata is considered expensive but valuable for performance and analytics capabilities in large-scale operations. Aurora, while also costly, is seen as cost-effective for improving cloud database performance, minimizing infrastructure investments. Both deliver ROI, with Teradata's justified higher costs emphasizing robust data processing, and Aurora's flexible pricing model appealing in the AWS ecosystem.

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

Amazon Aurora vs. Teradata

January 2025

Download the complete report

Helped 838,533 peers since 2012

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

Ranking in Relational Databases Tools

9th

Average Rating

8.2

Reviews Sentiment

6.5

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 (4th), Backup and Recovery (20th), Data Integration (16th), Data Warehouse (3rd), BI (Business Intelligence) Tools (10th), Marketing Management (6th), Cloud Data Warehouse (6th)

Mindshare comparison

As of February 2025, in the Relational Databases Tools category, the mindshare of Amazon Aurora is 3.4%, down from 4.3% compared to the previous year. The mindshare of Teradata is 5.5%, up from 5.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Relational Databases Tools

Featured Reviews

Rajitha Jatothu

Aws Devops Engineer at LTIMindtree

Achieve high performance with fault-tolerant and highly available database management

Aurora is a key pillar for us, offering performance and availability. It is faster than RDS and supports multi-region clusters and scalability. One feature we value is Aurora's ability to provide a reader endpoint, allowing applications to connect without tracking replicas. It supports auto-scaling and offers several options for monitoring and optimizing database performance. Aurora's fault tolerance and ability to handle multiple replicas contribute to its reliability and high performance.

Read full review

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.

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

"We had better control over the parameters that we could tweak in terms of intermediate storage and better indexing capabilities."

"Amazon Aurora stands out for its ease of use in a managed environment, inbuilt security, continuous backups, numerous read replicas, multi-region automated replication, and seamless integration with other AWS services."

"The most valuable feature is the ability to do multiple-read and single-write. These are the kinds of features that we were interested in, and Aurora takes care of that natively."

"The solution’s scalability is good since we don’t need to take a maintenance window during unpredictable workloads. I like the solution’s behind-the-scenes happenings. It is a great feature."

"The most valuable features of Amazon Aurora include the global instance with the global writer endpoint, which allows failovers and instance switches without requiring changes in my code, thanks to the default global Route 53 endpoint."

"The most valuable feature of Amazon Aurora is SQL standardization, it doesn't have its own syntax which is good. It has a lot of hands-off self-management type of activities, such as log rolling and auto-scaling."

"Aurora is a key pillar for us, offering performance and availability."

"Aurora's compatibility with MySQL or PostgreSQL benefited our database management. The migration from on-premise MySQL to Aurora was similar, so we didn't need to change our source code."

More Amazon Aurora pros

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

"The flexibility in design is very good."

"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."

"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."

"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."

"The most valuable features are the Shared-nothing architecture and data protection functionality."

"Teradata's best feature is its speed with historical data."

"It has a solid set of tools and consulting services."

More Teradata pros

Cons

"While Amazon Aurora meets your current scaling and storage needs, there is room for improvement in cryptography and scalability compared to other databases."

"It would have been helpful if they had provided some benchmarking numbers."

"In Oracle, tools like Veridata allow for comparing databases and certifying data accuracy, even offering repair capabilities, which are missing in Aurora. There should be a similar comparison tool in Aurora."

"The product's distributed query process for MySQL needs improvement."

"One of the most valuable features is storage scaling."

"There is improvement needed to have more developer focus. Additionally, it would be helpful to have a stand-alone solution outside of Amazon. Amazon has a tendency to favor developing web-based clients, which may not always provide the fastest or most responsive solution as desired."

"Room for improvement might be in the UI, integrations, or data working capabilities for better user experience."

"I would like to see more AI-related features in future releases."

More Amazon Aurora cons

"It is hard for some of our users to set up rules for cleansing and transforming data, so this is something that could be improved."

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

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

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

"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."

"The cloud is the new challenge and the new opportunity."

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

"The reporting side wasn't very good in the past, but with the latest versions, it's getting better. Still, the friendliness of the PDC reporting and functionality needs to be improved."

More Teradata cons

Pricing and Cost Advice

"The tool’s pricing depends on the instance type. For cost optimization purposes, we use the result instance category."

"The price could be lower compared to its competitors."

"It is quite expensive."

"There is no need to buy a license for the product. We can pay as per the use case."

"I would rate the pricing a six out of ten, with ten being expensive."

"It is an expensive solution."

"The cost is significantly high."

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

"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."

"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."

"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 solution requires a license."

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

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

More Teradata pricing and cost advice

See which vendors are best for you

Use our free recommendation engine to learn which Relational Databases Tools solutions are best for your needs.

See recommendations

838,533 professionals have used our research since 2012.

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

Financial Services Firm

27%

Computer Software Company

15%

Government

Manufacturing Company

Financial Services Firm

27%

Computer Software Company

10%

Manufacturing Company

Healthcare Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

Questions from the Community

What do you like most about Amazon Aurora?

Aurora's compatibility with MySQL or PostgreSQL benefited our database management. The migration from on-premise MySQL to Aurora was similar, so we didn't need to change our source code.

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

AWS is costlier than self-managed solutions, but this includes the managed service experience. Their pricing is fair and reflects the managed service and additional features AWS offers.

What needs improvement with Amazon Aurora?

AWS RDS doesn't provide an option to apply one-off patches, which can be critical for business due to unexpected product bugs. While self-managed systems allow immediate patch application, RDS has ...

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,...

SQL Server vs Amazon Aurora

Comparisons

Compared 38% of the time

Oracle Database vs Amazon Aurora

Compared 24% of the time

MariaDB vs Amazon Aurora

Compared 9% of the time

SAP HANA vs Amazon Aurora

Compared 6% of the time

CockroachDB vs Amazon Aurora

Compared 5% of the time

More Amazon Aurora Competitors

Oracle Exadata vs Teradata

Compared 14% of the time

SQL Server vs Teradata

Compared 11% of the time

MySQL vs Teradata

Compared 8% 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

Download Amazon Aurora product report

Amazon Aurora

February 2025

Download Teradata product report

January 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 is a MySQL and PostgreSQL-compatible relational database built for the cloud, that combines the performance and availability of traditional enterprise databases with the simplicity and cost-effectiveness of open source databases.

Amazon Aurora is up to five times faster than standard MySQL databases and three times faster than standard PostgreSQL databases. It provides the security, availability, and reliability of commercial databases at 1/10th the cost. Amazon Aurora is fully managed by Amazon Relational Database Service (RDS), which automates time-consuming administration tasks like hardware provisioning, database setup, patching, and backups.

Amazon Aurora features a distributed, fault-tolerant, self-healing storage system that auto-scales up to 64TB per database instance. It delivers high performance and availability with up to 15 low-latency read replicas, point-in-time recovery, continuous backup to Amazon S3, and replication across three Availability Zones (AZs).

Visit the Amazon RDS Management Console to create your first Aurora database instance and start migrating your MySQL and PostgreSQL databases.

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

Dow Jones, Arizona State University, Verizon, Capital One, United Nations, Nielsen, Autodesk, Fanduel

Netflix