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 compete in the data warehousing and analytics market. Microsoft appears to have the upper hand in affordability and integration with its ecosystem, while Teradata excels in predictive analytics and scalability.
Features: Microsoft Parallel Data Warehouse enhances performance and manages data efficiently within Microsoft products, offering easy integration. Teradata leverages advanced analytics, strong parallel processing for large volumes of data, and excellent data protection features.
Room for Improvement: Microsoft Parallel Data Warehouse requires improved integration with non-Microsoft BI tools and expertise for optimal use. Teradata faces high costs, a need to innovate in unstructured data management, and better cloud adoption and third-party tool integration.
Ease of Deployment and Customer Service: Microsoft Parallel Data Warehouse supports cloud and on-premises deployments, benefiting from Microsoft's extensive support, but relies on community resources. Teradata primarily deploys on-premises with cloud options, requiring more comprehensive support and a simplified deployment process.
Pricing and ROI: Microsoft Parallel Data Warehouse is cost-effective, especially with government agreements, while being seen as expensive for larger datasets. Teradata is costly, but offers strong performance for extensive data tasks; users are encouraged to consider costs carefully.
The technical support from Teradata is quite advanced.
Customer support is very good, rated eight out of ten under our essential agreement.
I give the scalability an eight out of ten, indicating it scales well for our needs.
This expansion can occur without incurring downtime or taking systems offline.
Scalability is complex as you need to purchase a license and coordinate with Teradata for additional disk space and CPU.
Microsoft Parallel Data Warehouse is stable for us because it is built on SQL Server.
I find the stability to be almost a ten out of ten.
The workload management and software maturity provide a reliable system.
When there are many users or many expensive queries, it can be very slow.
Microsoft Parallel Data Warehouse is excellent but very expensive.
The ETL designing process could be optimized for better efficiency.
Unlike SQL and Oracle, which have in-built replication capabilities, we don't have similar functionality with Teradata.
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.
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.
The interface is very user-friendly.
The data mover is valuable over the last two years as it allows us to achieve data replication to our disaster recovery systems.
The traditional structured relational data warehouse was never designed to handle the volume of exponential data growth, the variety of semi-structured and unstructured data types, or the velocity of real time data processing. Microsoft's SQL Server data warehouse solution integrates your traditional data warehouse with non-relational data and it can handle data of all sizes and types, with real-time performance.
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?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.
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