We performed a comparison between Snowflake and Teradata based on our users’ reviews in five categories. After reading all of the collected data, you can find our conclusion below.
Comparison Results: Both solutions received high marks from users. Snowflake comes out on top in this comparison. It is a powerful and reliable product that is easy to deploy. In addition, its users feel that it is reasonably priced.
"I like the idea that you can assign roles and responsibilities, limiting access to data."
"The tool's performance is good. I think it's the best in the game right now. It usually charges per query. For example, if you run a SQL query on Snowflake with the same number of data records, it would take less than half the time compared to running it on Microsoft. It has good documentation. You can pick up Snowflake if you have previous knowledge of SQL."
"Can be leveraged with respect to better performance, auto tuning and competition."
"It is a very well-distributed system. It has different data engines for different applications. Many applications can use different computational engines at the same time. In terms of data processing, the feeling was similar to working with a relational database but in a scalable way."
"The most valuable features of Snowflake are that you have to pay per usage, and you don't have to worry about the maintenance of the data warehouse because it is on the cloud."
"Time travel is one feature that really helps us out."
"The Time Travel feature is helpful for accessing historical data and the ability to clone external tables is useful."
"For us, the virtual warehousing is likely the most valuable aspect."
"The solution scales well on the cloud."
"Teradata's capabilities enhance data management efficiency, support scalability, and contribute to faster query performance."
"It is a stable program."
"Teradata features high productivity and reliability because it has several redundancy options, so the system is always up and running."
"I've never had any issues with scalability."
"Auto-partitioning and indexing, and resource allocation on the fly are key features."
"The performance is great, we are able to query our data in one operation."
"The most valuable features of Teradata are that it is a massively parallel platform and I can receive a lot of data and get the queries out correctly, especially if it's been appropriately designed. The native features make it very suitable for multiple large data tasks in a structured data environment. Additionally, the automation is very good."
"They need to improve its ETL functionality so that Snowflake becomes an ETL product. Snowpipe can do some pipelines and data ingestion, but as compare to Talend, these functionalities are limited. The ETL feature is not good enough. Therefore, Snowflake can only be used as a database. You can't use it as an ETL tool, which is a limitation. We have spoken to the vendor, and they said they are working on it, but I'm not sure when they will bring it to production."
"I would like to see more transparency in data processing, ATLs, and compute areas - which should give more comfort to the end users."
"There is a need for improvements in the documentation, this would allow more people to switch over to this solution."
"Pricing is an issue for many customers."
"The solution needs more connectors."
"There is room for improvement in Snowflake's integration with Python. We do a lot of SQL programming in Snowflake, but we go to a different tool to program when we have to in Python."
"Room for improvement would be writebacks. It doesn't support extensively writing back to the database, and it doesn't support web applications effectively. Ultimately, it's a database call, so if we are building web applications using Snowflake, it isn't that effective because there is some turnaround time from the database."
"The data science functionality could be improved in terms of the machine learning process."
"An additional feature I would you like to see included in the next release, is that it needs to be more cloud-friendly."
"The current operational approach needs improvement."
"We tried to use case Teradata for a data warehouse system, but we had some problems in relation to the Teradata system, CDC tools, and source databases. We were unable to transfer data from HPE Integrity mainframe to Teradata."
"Teradata could improve by being less complicated. There are some aspects that are not available on the Unix server and a Unix system is required to access some data, such as in case of an emergency."
"The setup is not straightforward."
"GUI of administrative tools is really outdated."
"The following could be better: licensing, architecture openness, integration with other tools."
"Data ingestion is done via external utilities and not by the query language itself. It would be more convenient to have that functionality within its SQL dialect."
Snowflake is ranked 1st in Data Warehouse with 94 reviews while Teradata is ranked 3rd in Data Warehouse with 54 reviews. Snowflake is rated 8.4, while Teradata is rated 8.2. The top reviewer of Snowflake writes "Good usability, good data sharing and elastic compute features, and requires less DBA involvement". On the other hand, the top reviewer of Teradata writes "Offers seamless integration capabilities and performance optimization features, including extensive indexing and advanced tuning capabilities". Snowflake is most compared with BigQuery, Azure Data Factory, Vertica, AWS Lake Formation and Oracle Autonomous Data Warehouse, whereas Teradata is most compared with SQL Server, Oracle Exadata, MySQL, BigQuery and IBM Db2 Database. See our Snowflake vs. Teradata report.
See our list of best Data Warehouse vendors and best Cloud Data Warehouse vendors.
We monitor all Data Warehouse reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.