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Snowflake's ease of use allows you to focus on what matters most - the data you're filling it with
June 10, 2019

Snowflake's ease of use allows you to focus on what matters most - the data you're filling it with

Andrew Goss | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User

Overall Satisfaction with Snowflake

My company adopted Snowflake as our first cloud-based data warehouse. It is being used as a central repository for all company data from each business unit for the purposes of business intelligence.
  • Ease of use
  • Separation of storage and compute resources
  • Simple to scale up or down with virtual warehouses
  • Built-in support for the most popular data formats
  • Standard SQL dialect
  • Robust function library
  • Lacks support for common table expressions
  • Lacks support for correlated subqueries
  • Better technical support for customer identified bugs
  • Clearer pricing model
  • Centralized disparate data sources across the company
  • Used to associate fragmented and unlock key insights
  • Integrates easily with our business intelligence tool, Sisense
The average percentage of time that a data warehouse is actually doing something is around 20%. Given this, the price by query estimate becomes an important pricing consideration.

For this, Snowflake crucially decouples of storage and compute. With Snowflake you pay for 1) storage space used and 2) amount of time spent querying data. Snowflake also has a notion of a “logical warehouse” which is the “compute” aspect of the database. These warehouses can be scaled up or down to deliver different grades of performance. You can also configure the number of compute nodes to parallelize query execution. These warehouses can be configured to “pause” when you’re not using them for cost efficiency. As a result, you can have a super beefy warehouse for BI queries that’s only running when people are using your BI tools, while your background batch jobs can use cheaper hardware.
Clean user interface - designed to be relatively easy to find what you're looking for. Strong supporting documentation. Built-in query optimizer allows you to simply focus more on pure data crunching instead of performance tuning.
Snowflake architecture was designed at its foundation to take advantage of the cloud and then adds some unique benefits that support ease of use and increased productivity. The most popular cloud data warehouse platforms are all powerful tools and solid choices. With an investment in one of these, what really matters is how productive will you be using the data warehouse.

Snowflake's 'data-warehouse-as-a-service' model lessens the maintenance tasks of optimization/tuning that have traditionally fallen to DBAs and ETL developers. There are no servers to manage, software to install, or indexes to tune. This allows data engineers and analysts to focus more exclusively on analytic tasks that will translate into growth for the company.

While Snowflake doesn’t have all the performance optimization bells and whistles of other cloud data warehouse platforms, this is actually a good thing and that most people don't really need all of them or miss them. Using Snowflake on the whole means less knob-turning and futzing with setup/tweaking. Snowflake has its query optimizer already built-in.