Teradata and Snowflake are key competitors in the data warehousing category. Snowflake seems to have the upper hand with its flexibility, ease of scaling, and efficient pricing model.
Features: Teradata is known for its efficient handling of large data volumes with features like the smart Teradata Optimizer, massively parallel processing architecture, and a shared-nothing architecture for high scalability. Snowflake offers flexibility in scaling, the ability to handle semi-structured data, and a pay-per-second pricing model. It includes automatic scaling and separation of compute and storage.
Room for Improvement: Teradata is often criticized for its high cost and complexity in scalability. Users also note limitations in managing unstructured data and cloud readiness. Snowflake users find room for improvement in managing real-time and transactional data and note challenges with cost estimation at scale. Its machine learning and AI functionalities are seen as needing development.
Ease of Deployment and Customer Service: Teradata is typically deployed in on-premises and hybrid cloud setups. It receives mixed reviews for customer service, with some users praising its support network and others noting slow response times. Snowflake is predominantly on public clouds, offering flexibility in scaling and integration. It is praised for quick resolution times and efficient online resources.
Pricing and ROI: Teradata's premium pricing is justified by its performance and reliability but is considered high. Snowflake's flexible usage-based pricing aligns well with cloud cost structures, aiding efficient cost management, though there are concerns about predictability at scale. Both show strong ROI, tailored to different scenarios with Snowflake's agile pricing and Teradata's robust performance.
I received great support in migrating data to Snowflake, with quick responses and innovative solutions.
The technical support from Snowflake is very good, nice, and efficient.
The technical support from Teradata is quite advanced.
Customer support is very good, rated eight out of ten under our essential agreement.
Snowflake is very scalable and has a dedicated team constantly improving the product.
The billing doubles with size increase, but processing does not necessarily speed up accordingly.
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.
Snowflake is very stable, especially when used with AWS.
Snowflake as a SaaS offering means that maintenance isn't an issue for me.
I find the stability to be almost a ten out of ten.
The workload management and software maturity provide a reliable system.
Enhancements in user experience for data observability and quality checks would be beneficial, as these tasks currently require SQL coding, which might be challenging for some users.
Cost reduction is one area I would like Snowflake to improve.
Unlike SQL and Oracle, which have in-built replication capabilities, we don't have similar functionality with Teradata.
Snowflake's pricing is on the higher side.
Snowflake lacks transparency in estimating resource usage.
Initially, it may seem expensive compared to similar cloud databases, however, it offers significant value in performance, stability, and overall output once in use.
Teradata is much more expensive than SQL, which is well-performed and cheaper.
Snowflake is a data lake on the cloud where all processing happens in memory, resulting in very fast query responses.
Being able to perform AI and Machine Learning in the same location as the data is quite advantageous.
The data mover is valuable over the last two years as it allows us to achieve data replication to our disaster recovery systems.
Snowflake provides a modern data warehousing solution with features designed for seamless integration, scalability, and consumption-based pricing. It handles large datasets efficiently, making it a market leader for businesses migrating to the cloud.
Snowflake offers a flexible architecture that separates storage and compute resources, supporting efficient ETL jobs. Known for scalability and ease of use, it features built-in time zone conversion and robust data sharing capabilities. Its enhanced security, performance, and ability to handle semi-structured data are notable. Users suggest improvements in UI, pricing, on-premises integration, and data science functions, while calling for better transaction performance and machine learning capabilities. Users benefit from effective SQL querying, real-time analytics, and sharing options, supporting comprehensive data analysis with tools like Tableau and Power BI.
What are Snowflake's Key Features?In industries like finance, healthcare, and retail, Snowflake's flexible data warehousing and analytics capabilities facilitate cloud migration, streamline data storage, and allow organizations to consolidate data from multiple sources for advanced insights and AI-driven strategies. Its integration with analytics tools supports comprehensive data analysis and reporting tasks.
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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