

Teradata and Snowflake are competitors in the data warehousing category. Snowflake appears to have the upper hand due to its flexibility and scalability, which are beneficial for businesses looking to expand dynamically without hefty costs.
Features: Teradata offers massively parallel processing, robust tools for handling large datasets, and performance optimization for structured data environments. Its shared-nothing architecture enhances scalability and real-time data analysis. Snowflake provides seamless scalability, pay-as-you-go pricing, and easy data sharing. It supports semi-structured and unstructured data, harnessing cloud capabilities for rapid adjustments based on workload demands. The solution offers time travel and zero-copy cloning as additional flexible features.
Room for Improvement: Teradata needs to enhance data synchronization, query response times, and cloud transition. Customers recommend improving licensing and cost scalability. Snowflake could benefit from enhanced pricing transparency and analytical functionalities. Expanding machine learning capabilities and improving the user interface are also areas for Snowflake to work on.
Ease of Deployment and Customer Service: Teradata provides on-premises and hybrid solutions, but its cloud transition lags. It is noted for strong technical support, although response times could be enhanced. Snowflake's cloud-native design simplifies deployment across cloud platforms with consistent service, yet improving response times for technical support would elevate customer satisfaction.
Pricing and ROI: Both solutions offer substantial ROI. However, Snowflake's usage-based pricing offers more flexibility and cost-effectiveness for scalable needs. Teradata's pricing is higher, justified by its performance in large enterprises. Snowflake holds an advantage with straightforward pricing, despite some transparency concerns.
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%.
I received great support in migrating data to Snowflake, with quick responses and innovative solutions.
I am satisfied with the work of technical support from Snowflake; they are responsive and helpful.
The technical support from Snowflake is very good, nice, and efficient.
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.
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.
Recently, Snowflake has introduced streaming capabilities, real-time and dynamic tables, along with various connectors.
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.
Snowflake is very stable, especially when used with AWS.
Snowflake as a SaaS offering means that maintenance isn't an issue for me.
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.
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.
What things you are going with to ask the support and how we manage the relationship matters a lot.
If more connectors were brought in and more visibility features were added, particularly around cost tracking in the FinOps area, it would be beneficial.
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.
Snowflake's pricing is on the higher side.
Snowflake lacks transparency in estimating resource usage.
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.
We had a comparison with Databricks and Snowflake a few months back, and this auto-scaling takes an edge within Snowflake; that's what our observation reflects.
I have used the Snowflake Zero-Copy Cloning feature in the past while prototyping data in lower environments. This feature is helpful as it saves a lot of time during the data replication process.
Snowflake is a data lake on the cloud where all processing happens in memory, resulting in very fast query responses.
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 | Market Share (%) |
|---|---|
| Snowflake | 10.7% |
| Teradata | 10.3% |
| Other | 79.0% |


| Company Size | Count |
|---|---|
| Small Business | 29 |
| Midsize Enterprise | 20 |
| Large Enterprise | 57 |
| Company Size | Count |
|---|---|
| Small Business | 28 |
| Midsize Enterprise | 13 |
| Large Enterprise | 52 |
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?
What Benefits Should You Look for?
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 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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