What is Snowflake?
Snowflake is a US cloud computing data warehousing company. The publicly-traded company was founded in 2012 and has a market capitalization of $100B as of December 2021.
Snowflake technology enables its clients to "build data-intensive applications without operational burden." In practice, Snowflake facilitates the storage of massive amounts of data in the cloud and access to it in a scalable and efficient way.
Snowflake states that its technology unlocks-
Ease of Use
Performance
Instant Elasticity
Utility Model
Data Volume
In many ways, Snowflake can be an alternative and a complement to Amazon Redshift, Google BigQuery, and Microsoft Azure.
Why should you care about Cloud Data Warehousing and Sharing?
Spreadsheets and APIs are great, but Spreadsheets were not built to store and work on massive amounts of data, while APIs were not built to pull such large volumes either. As with everything, each technology and solution has merits, use cases, and limitations.
What is DataHawk's Data Sharing solution for Snowflake?
DataHawk can automatically store and keep in sync all your DataHawk account's data on a Snowflake cloud data warehouse in a turnkey plug-and-play fashion. Thanks to DataHawk for the Snowflake solution, you can
Access hosted data tables containing your DataHawk account data
Directly use SQL queries to pull data in structured tables format
Keep the data stored on Snowflake or move it to another data warehouse
Create custom dashboards and data visualizations
Below is an example of a DataHawk table containing keywords search results that can be accessed on Snowflake. As you can notice, data is already provided in a clean table format by design, and the only thing required to access it is a SQL query.
How does DataHawk's Data Sharing solution for Snowflake differ from using an API?
An API (Application Program Interface) facilitates data exchange between two apps. Thanks to DataHawk's API, you can
Use our API endpoints to pull data in a structured JSON format
Use our API endpoints to make edits to your DataHawk account
With extra work, store the data you pull in your own data warehouse
Set up an orchestration workflow to automate the process as needed
Create custom dashboards and data visualizations
Using an API has volume limitations
One big limitation of an API is its inadequacy with big data use cases, when one needs to fetch massive amounts of data, especially at a high frequency. That is why a principle of "rate limits" exists on APIs to ensure they can provide an optimal quality of service and security.
At DataHawk, our API has a rate limit of 500 calls per 15 sliding minutes, i.e., a limit of 500 x 96 = 48,000 daily calls. In other words, you can make 500 requests to our API every 15 minutes.
In other words, using our API solution may limit the volume and frequency of data you can pull, while using our Snowflake solution doesn't.
Using an API requires a lot of work to implement and maintain
Another major consideration of using an API is that it requires engineering time to implement the orchestration and storage workflows.
Indeed, as you make an API call to pull data, you get results in a JSON format and still need to
Parse and format the results
Create rules to programmatically transfer that data to a storage destination
Create rules to automatically repeat the process and keep the data in sync
In other words, it is much simpler to access your DataHawk data on Snowflake or even pull it from Snowflake to your warehouse than to pull the data from our API to your warehouse.
How would I access data using DataHawk for Snowflake?
You can set up your DataHawk-powered Snowflake warehouse in a few minutes.
Head to the Connections page on your DataHawk account and add Snowflake as a Destination.
Your credentials will be generated after a few minutes.
You can then use these Credentials to access your cloud warehouse.
You can read more about DataHawk Connections and syncing data with Snowflake and Business Intelligence solutions here.
What is the cost of DataHawk for Snowflake?
The Starter and Growth plans include access to DataHawk's Database solution on Snowflake with a predetermined volume of computation capacity that should cover the needs of most brands within those plans.
When computation needs surpass the default values provided in a plan, it is possible to increase them by talking to sales.
To learn more about the DataHawk Subscription plans, click here.