

Teradata and Amazon Aurora compete in the robust data management and analytics solutions category. Based on features, Aurora has the upper hand due to its seamless AWS integration and cost efficiency.
Features: Teradata is known for its parallel processing capabilities, MPP architecture, and suitability for complex data environments. Amazon Aurora offers auto-scaling, low-latency replication, and seamless integration with AWS, providing cost efficiency and high performance.
Room for Improvement: Teradata needs to improve cloud adoption, unstructured data handling, and integration with AI. Amazon Aurora can enhance its developer-focused features, cryptographic capabilities, and reduce high per-hour usage costs.
Ease of Deployment and Customer Service: Teradata provides flexible deployment but is seen as complex and expensive. Aurora is praised for easy deployment in AWS, efficient scaling, and offers excellent customer support.
Pricing and ROI: Teradata, though high-cost, provides strong ROI for large enterprises. Aurora's pay-as-you-go model is more cost-effective, favored where scalability and cost control are priorities.
Using Amazon Aurora has saved us significantly in terms of manpower costs, with nearly fifty percent savings compared to an on-premises solution.
At least fifteen to twenty percent of our time has been saved using Teradata, which has positively affected team productivity and business outcomes.
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.
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%.
Technical support from Amazon is rated very highly.
The initial support could improve by having engineers familiarize themselves with the issue content to provide more specialized assistance from the start.
The customer support for Teradata has been great.
They are responsive and knowledgeable, and the documentation is very helpful.
Customer support is very good, rated eight out of ten under our essential agreement.
This scalability is critical as it allows for runtime expansion, which is essential for businesses moving from on-premises to the cloud.
Regarding scalability and the ability to scale, I would give it a 9.5 out of ten.
Whenever we need more resources, we can add that in Teradata, and when not needed, we can scale it down as well.
This flexibility allows organizations to scale according to their needs, balancing performance, cost, and compliance requirements.
This expansion can occur without incurring downtime or taking systems offline.
It offers a stable environment, ensuring consistent performance.
I would rate the stability of Amazon Aurora as a nine out of ten.
Its massively parallel process architecture allows the platform to distribute workload efficiently, enabling organizations to run heavy analytic queries without compromising speed or stability.
I find the stability to be almost a ten out of ten.
The workload management and software maturity provide a reliable system.
There are technical challenges, such as the inability to provision the database using a PostgreSQL snapshot directly.
Keeping extensions up-to-date with PostgreSQL releases would enhance Aurora's functionality.
A cost reduction would support multiple teams to adopt this solution since the cost is currently higher.
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.
Unlike SQL and Oracle, which have in-built replication capabilities, we don't have similar functionality with Teradata.
The most challenging aspect is finding Teradata resources, so we are focusing on internal training and looking for more Teradata experts.
The pricing is reasonable and not overly expensive.
Amazon Aurora is not very expensive as other solutions with similar features from other vendors come at almost the same cost.
The pricing for Amazon Aurora is different from DocumentDB because DocumentDB is cheaper.
Teradata is much more expensive than SQL, which is well-performed and cheaper.
Initially, it may seem expensive compared to similar cloud databases, however, it offers significant value in performance, stability, and overall output once in use.
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.
Amazon Aurora offers a 99.9% SLA compared to PostgreSQL. This ensures a high level of availability for our applications.
It replicates data across multiple Availability Zones, ensuring high availability and geographical redundancy, which can be considered a GR instead of a DR.
The functions I have found most valuable in Amazon Aurora PostgreSQL are features that are not available in normal RDS PostgreSQL, particularly for scaling and restoration purposes in the event of failure.
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.
Its architecture allows information to be processed efficiently while maintaining stable performance, even in highly demanding environments.
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.
| Product | Mindshare (%) |
|---|---|
| Teradata | 4.1% |
| Amazon Aurora | 3.2% |
| Other | 92.7% |


| Company Size | Count |
|---|---|
| Small Business | 5 |
| Midsize Enterprise | 4 |
| Large Enterprise | 14 |
| Company Size | Count |
|---|---|
| Small Business | 28 |
| Midsize Enterprise | 13 |
| Large Enterprise | 52 |
Amazon Aurora offers a relational database service with high availability and compatibility with MySQL and PostgreSQL. It is designed for efficient scalability and seamless integration within AWS, making it optimal for applications requiring robust performance and reliability.
Amazon Aurora distinguishes itself through its managed maintenance, ensuring high operational efficiency. It provides users with the ability to auto-scale their database resources, allowing businesses to maintain cost efficiency without sacrificing performance. The service includes robust disaster recovery options and supports up to sixteen read replicas, which are critical for mission-critical applications. Users benefit from smooth, cross-region replication and integration capabilities with other AWS services, enhancing data reliability and accessibility.
What are the most important features of Amazon Aurora?Amazon Aurora is extensively used across various industries such as finance, e-commerce, and healthcare, supporting internal applications with its relational database prowess. Many organizations leverage its serverless capabilities and cost-effective scalability for developing business intelligence and payment processing solutions. The seamless migration assistance from Oracle databases further underscores its appeal for enterprises looking to optimize database performance and reduce operational costs.
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?
What benefits and ROI do users look for?
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.
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