Teradata and Snowflake compete in the data warehousing sector. Based on feature analysis, Teradata holds an edge with extensive query processing and workload management capabilities, while Snowflake excels in user-friendliness and scalability.
Features: Teradata has Viewpoint for performance tracking, a shared-nothing architecture, and TASM for workload management, handling large datasets with ease. Snowflake offers zero-copy cloning, time travel for data retrieval, and a separation of storage and computing resources, providing dynamic scaling and cost efficiency.
Room for Improvement: Teradata could improve by reducing high costs, updating its interface, and enhancing cloud compatibility, along with better support for unstructured data. Snowflake can enhance machine learning support and simplify its pricing model for easier cost estimation. Both solutions can benefit from improved integrations and user-friendly interfaces.
Ease of Deployment and Customer Service: Teradata focuses on hybrid and on-premises deployment, offering extensive resources like Teradata University but faces delays in technical support. Snowflake, optimized for cloud deployment, emphasizes easy setup with efficient customer service, suiting cloud-native operations better.
Pricing and ROI: Teradata is known for high costs but offers flexible pricing, such as pay-as-you-go, suitable for large enterprises. Snowflake offers a competitive pay-as-you-go model, appealing to businesses seeking cost transparency and scalability. It balances affordability with robust cloud features, ensuring high value for consumption-based models.
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 is a cloud-based data warehousing solution for storing and processing data, generating reports and dashboards, and as a BI reporting source. It is used for optimizing costs and using financial data, as well as for migrating data from on-premises to the cloud. The solution is often used as a centralized data warehouse, combining data from multiple sources.
Snowflake has helped organizations improve query performance, store and process JSON and XML, consolidate multiple databases into one unified table, power company-wide dashboards, increase productivity, reduce processing time, and have easy maintenance with good technical support.
Its platform is made up of three components:
Snowflake has many valuable vital features. Some of the most useful ones include:
There are many benefits to implementing Snowflake. It helps optimize costs, reduce downtime, improve operational efficiency, and automate data replication for fast recovery, and it is built for high reliability and availability.
Below are quotes from interviews we conducted with users currently using the Snowflake solution:
Sreenivasan R., Director of Data Architecture and Engineering at Decision Minds, says, "Data sharing is a good feature. It is a majorly used feature. The elastic computing is another big feature. Separating computing and storage gives you flexibility. It doesn't require much DBA involvement because it doesn't need any performance tuning. We are not doing any performance tuning, and the entire burden of performance and SQL tuning is on Snowflake. Its usability is very good. I don't need to ramp up any user, and its onboarding is easier. You just onboard the user, and you are done with it. There are simple SQL and UI, and people are able to use this solution easily. Ease of use is a big thing in Snowflake."
A director of business operations at a logistics company mentions, "It requires no maintenance on our part. They handle all that. The speed is phenomenal. The pricing isn't really anything more than what you would be paying for a SQL server license or another tool to execute the same thing. We have zero maintenance on our side to do anything and the speed at which it performs queries and loads the data is amazing. It handles unstructured data extremely well, too. So, if the data is in a JSON array or an XML, it handles that super well."
A Solution Architect at a wholesaler/distributor comments, "The ability to share the data and the ability to scale up and down easily are the most valuable features. The concept of data sharing and data plumbing made it very easy to provide and share data. The ability to refresh your Dev or QA just by doing a clone is also valuable. It has the dynamic scale up and scale down feature. Development and deployment are much easier as compared to other platforms where you have to go through a lot of stuff. With a tool like DBT, you can do modeling and transformation within a single tool and deploy to Snowflake. It provides continuous deployment and continuous integration abilities. There is a separation of storage and compute, so you only get charged for your usage. You only pay for what you use. When we share the data downstream with business partners, we can specifically create compute for them, and we can charge back the business."
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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