Apr 13, 2014
I think hands down it's Exadata since for the front end apps it's just another Oracle database which means everything under the sun is compatible with it.
Microsoft Parallel Data Warehouse and Teradata both compete in the data warehousing and analytics category. Based on comparisons, Teradata appears to have the upper hand due to its stronger capabilities in handling complex queries quickly and efficiently.
Features: Microsoft Parallel Data Warehouse integrates well with the Microsoft ecosystem, handling large data volumes efficiently and boosting data processing speed while remaining user-friendly. Teradata is robust in data analytics, has high-speed processing capabilities, and handles complex queries efficiently, making it suitable for large-scale requirements.
Room for Improvement: Microsoft Parallel Data Warehouse could improve in integrating with non-Microsoft tools, simplifying configuration processes, and enhancing its BI layer. Teradata could benefit from better cloud offerings, cost reductions, and enhanced handling of unstructured data, as well as broader deployment flexibility.
Ease of Deployment and Customer Service: Microsoft Parallel Data Warehouse offers flexible deployment across cloud and on-premises, with generally satisfactory customer service. Teradata provides robust deployment options for complex settings, but users indicate a need for more intuitive interfaces and expanded customer support.
Pricing and ROI: Microsoft Parallel Data Warehouse is cost-effective for extensive data ecosystems but pricier for smaller applications. Its seamless integration is a cost-benefit factor. Teradata, though considered high-priced, brings significant value with its advanced features and performance in large-scale data contexts, but its initial and operational costs are frequently viewed as high.
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%.
They are responsive and get back to us.
I would rate my experience with technical support around six on a scale of 1 to 10 because I have not had a particular experience with technical support.
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.
We go from a couple of users to tons of users all the time, and it scales and handles things really well.
I give the scalability an eight out of ten, indicating it scales well for our needs.
As a consultant, we hire additional programmers when we need to scale up certain major projects.
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.
Microsoft Parallel Data Warehouse is stable for us because it is built on SQL Server.
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.
It would be better to release patches less frequently, maybe once a month or once every two months.
Addressing the cost would be the number one area for improvement.
When there are many users or many expensive queries, it can be very slow.
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.
Microsoft Parallel Data Warehouse is very expensive.
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.
The columnstore index enhances data query performance by using less space and achieving faster performance than general indexing.
Microsoft Parallel Data Warehouse is used in the logistics area for optimizing SQL queries related to the loading and unloading of trucks.
There's a feature that allows users to set alerts on triggers within reports, enabling timely actions on pending applications and effectively reducing waiting time.
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 | 8.8% |
| Microsoft Parallel Data Warehouse | 3.2% |
| Other | 88.0% |
| Company Size | Count |
|---|---|
| Small Business | 16 |
| Midsize Enterprise | 6 |
| Large Enterprise | 22 |
| Company Size | Count |
|---|---|
| Small Business | 28 |
| Midsize Enterprise | 13 |
| Large Enterprise | 52 |
Microsoft Parallel Data Warehouse offers high performance and usability with seamless SQL Server integration, handling large data efficiently with a user-friendly interface. Known for its cost-effectiveness and robust security, it excels in integrating data across Microsoft ecosystem.
Microsoft Parallel Data Warehouse efficiently manages large datasets from diverse sources, supporting a unified data approach. Its integration with SQL Server and compatibility with tools like Qlik enhances data management and decision-making capabilities. With impressive scalability and security features, it is widely used in sectors such as finance, healthcare, and logistics for analytics and reporting. However, users seek improvements in integration with non-Microsoft layers, memory usage, SQL configuration, and scalability.
What are the key features of Microsoft Parallel Data Warehouse?In industries like finance, healthcare, and logistics, Microsoft Parallel Data Warehouse supports analytics, reporting, and decision-making processes. Organizations utilize it to maintain historical data, develop business intelligence models, and create actionable dashboards, benefiting from its integration with key tools and efficient data management.
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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