Item: Snowflake
Rating: 10
Author: Jeremy Pierce, MBA

Overall Satisfaction with Snowflake

Use Cases and Deployment Scope

We use Snowflake in our organization as both our data lake & data warehouse. Instead of ETLing from source to a data lake to then architect our data, we have made internal schemas that we can ETL the data into. We then use an on-prem SQL Server to execute our SSIS packages, which support a DSN connection.

So far it's been very easy and very successful.

Pros and Cons

Pros

Processing speed
Scaling warehouses
Ease of use

Cons

Hard to say, they're adding new features all the time.
I feel like Snowflake's documentation is a little too thorough, it can be hard to understand
I'm not a fan of the web interface, I use DBeaver instead.

Most Important Features

Speed of execution - you can write some UGLY queries and they'll still execute fast
Reliability - no more bugging a DBA to restart a server that's out of resources at 7pm
Ease of implementation - Snowflake was fantastic to work with every step of the way

Return on Investment

I can't speak to ROI as I can't see the numbers, but my Sr. Director is thrilled with the cost.
Since implementing Snowflake we've been able to hire 3 new engineers to help share the workload.
Transitioning to Snowflake allowed us to get all of the company on 1 source of truth.

Alternatives Considered

Microsoft SQL Server

We had a MS SQL server with over 2 TB of ram & 51 processors that we were using, that could no longer handle our workload. Snowflake can handle 3 times that workload with ease and efficiency.

Key Insights

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

Other Software Used

DBeaver, Cyberduck, GoAnywhere MFT

Likelihood to Recommend

I am over our HR data, and we use Workday for our HR management system.

I have a script in place that runs reports on Workday and saves the results as CSVs. I can then use stages in Snowflake to insert these CSVs into Snowflake, then I can insert or truncate and replace these staged tables into a final schema. Then once these are in a schema I can reference them and build out my data models. In addition to ingesting CSVs, Snowflake has the ability to write a CSV file to our Amazon S3 bucket.

Ingesting these CSVs, transforming the data, then delivering it to a destination would've involved so much more coding than my current process if we were on any other platform.

Comments

Please log in to join the conversation

Don't debate, just migrate to Snowflake already.