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Snowflake enables data pull for all levels of analysts
Updated November 23, 2021

Snowflake enables data pull for all levels of analysts

Anonymous | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User

Overall Satisfaction with Snowflake

My company switched from Amazon Redshift to Snowflake a while ago, and we got a huge improvement in data to pull by using Snowflake. The tool is widely used in multiple departments within the company and people with all level of data science skill and retrieve the data easily by using SQL.
  • data pull
  • access management
  • data transfer
  • speed
  • data type
  • better integration
  • integrate analyst
  • paralleling work within team
  • remove bottleneck
Since we switch from Amazon Redshift to Snowflake, we found Snowflake is much better than redshift in many ways, including the data integrate and data pull. However, comparing directly pull data from Amazon S3, Snowflake is quite slow in terms of data pull speed and the more method to process data in python.
Overall, the support from Snowflake has been very good. Since we are one of the major users for Snowflake and have a dedicated tech team to solve all the technical problem on our way. On the side of the technical problem, any sql related questions can be found from everywhere online.

Do you think Snowflake delivers good value for the price?

Yes

Are you happy with Snowflake's feature set?

Yes

Did Snowflake live up to sales and marketing promises?

Yes

Did implementation of Snowflake go as expected?

Yes

Would you buy Snowflake again?

Yes

Atom, Docker, PyCharm
Snowflake is suitable for the situations that you are working with all levels of analysts in terms of data science skills. By using SQL, the user does not need to understand data type, etc. before using the tool. However, it could be potential trouble when consuming the data in python later.