More of a big picture question, but is cloud storage predicted to just endlessly grow? In other words, will there ever be an alternative that is as cheap and effective as cloud storage?
Very dependent on who you ask and it is tough to predict. There is some terminal value risk if a disruptive innovation comes along, but I think that is similar to almost every industry. I have also seen some opinions where people think cloud storage is the "end state".
What do you mean when you say Snowflake can connect to Oracle or GCP/AWS/Azure sources? As far as I know, there's no real external/federated query capabilities on Snowflake. If you were trying to read directly out of an Oracle DB on prem / a CloudSQL GCP MySQL instance / an RDS AWS Postgres instance, you'd have to replicate the data into Snowflake using some process (script, Snowpipe, 3rd party ETL tool, etc.)
You mentioned in the article that the three majors only can read on-prem data + whatever's in their cloud - I don't think that's really true. BigQuery Omni can read across all three major cloud object storage platforms (https://cloud.google.com/blog/products/data-analytics/analyze-data-across-clouds-with-bigquery-omni), and while I don't have experience with it, it looks like Athena has multi-cloud capabilities on the AWS side, too.
Finally, I'd just mention that as of right now (6/8/22), Python Snowpark is in private preview, AKA not generally available. Hopefully that changes soon, but as of right now I think most customers either don't have access, or would be skeptical to build production workflows on a product which is essentially in beta.
1. In regards to Snowflake's ability to connect to Oracle or GCP/AWS/Azure I meant its ability to replicate data into Snowflake and use a process.
2. In my due diligence, I missed BigQuery Omni. I have corrected the article to include that service. From my research, AWS Athena has multi-cloud capabilities, but from what I have seen Amazon describes it as an "interactive query service" not a data warehouse. I have not used Athena myself, but believe Redshift should be the direct comparison to Snowflake.
3. I added a note that Python Snowpark is in private preview.
Hey man, liked you writeup but this seems wrong "Stock-based compensation is adjusted out of the operating income. While it is a real expense, it is already factored into the diluted shares outstanding projections in the final table." In my view, SBC = pay cash to employee + finance the cash with equity issuance. So taking the expense to P&L and dilute the shares isn't double counting
Hi Zeyu, Thank you! SBC is a non-cash expense. The company does not give up any cash when paying an employee SBC. The share count does increase (making the other shares less valuable). The increase in share count is factored into the final diluted shares outstanding table, but the company does not physically pay out any cash. I hope this clarifies it. If not, I have included a link to an article with more detail on handling SBC. https://corporatefinanceinstitute.com/resources/knowledge/accounting/share-stock-based-compensation/
Fascinating points regarding the stickiness of the Snowflake products.
Something of interest, I wasn't aware that competing AWS and Azure products would only interface with on premise data sources. I haven't dove deep into these limitations as provided by AWS and Azure, but at the same time, my light initial research has led me to believe that data could be moved from on premise environments into AWS and Azure products for the purpose of being consumed by Redshift or Synapse. I would image you are quite busy, but it would be pretty awesome if you could expound on that particular limitation of Redshift and Synapse as it pertains to these products being behind Snowflake in this regard.
Hi Owen, Thank you for the comment. AWS and Azure have the ability to do database migration projects (similar to Snowflake) and be consumed by their own data warehouse products. Where Snowflake differentiates itself, is that it can connect AWS and Azure cloud storage, while AWS and Azure are not compatible with each other. This creates the problem of data silos as most companies have data in both AWS and Azure and the data cannot connect together. I hope this clarifies it.
I liked your statistics "% of customers using data sharing." That is a good metric. Also compelling that you have have first hand experience with a data migration to Snowflake! 👍
More of a big picture question, but is cloud storage predicted to just endlessly grow? In other words, will there ever be an alternative that is as cheap and effective as cloud storage?
Very dependent on who you ask and it is tough to predict. There is some terminal value risk if a disruptive innovation comes along, but I think that is similar to almost every industry. I have also seen some opinions where people think cloud storage is the "end state".
Hey, liked the article but I have some thoughts:
What do you mean when you say Snowflake can connect to Oracle or GCP/AWS/Azure sources? As far as I know, there's no real external/federated query capabilities on Snowflake. If you were trying to read directly out of an Oracle DB on prem / a CloudSQL GCP MySQL instance / an RDS AWS Postgres instance, you'd have to replicate the data into Snowflake using some process (script, Snowpipe, 3rd party ETL tool, etc.)
You mentioned in the article that the three majors only can read on-prem data + whatever's in their cloud - I don't think that's really true. BigQuery Omni can read across all three major cloud object storage platforms (https://cloud.google.com/blog/products/data-analytics/analyze-data-across-clouds-with-bigquery-omni), and while I don't have experience with it, it looks like Athena has multi-cloud capabilities on the AWS side, too.
Finally, I'd just mention that as of right now (6/8/22), Python Snowpark is in private preview, AKA not generally available. Hopefully that changes soon, but as of right now I think most customers either don't have access, or would be skeptical to build production workflows on a product which is essentially in beta.
Hi Dan, thank you for the comment.
1. In regards to Snowflake's ability to connect to Oracle or GCP/AWS/Azure I meant its ability to replicate data into Snowflake and use a process.
2. In my due diligence, I missed BigQuery Omni. I have corrected the article to include that service. From my research, AWS Athena has multi-cloud capabilities, but from what I have seen Amazon describes it as an "interactive query service" not a data warehouse. I have not used Athena myself, but believe Redshift should be the direct comparison to Snowflake.
3. I added a note that Python Snowpark is in private preview.
Thank you for the comment.
Hey man, liked you writeup but this seems wrong "Stock-based compensation is adjusted out of the operating income. While it is a real expense, it is already factored into the diluted shares outstanding projections in the final table." In my view, SBC = pay cash to employee + finance the cash with equity issuance. So taking the expense to P&L and dilute the shares isn't double counting
Hi Zeyu, Thank you! SBC is a non-cash expense. The company does not give up any cash when paying an employee SBC. The share count does increase (making the other shares less valuable). The increase in share count is factored into the final diluted shares outstanding table, but the company does not physically pay out any cash. I hope this clarifies it. If not, I have included a link to an article with more detail on handling SBC. https://corporatefinanceinstitute.com/resources/knowledge/accounting/share-stock-based-compensation/
Fascinating points regarding the stickiness of the Snowflake products.
Something of interest, I wasn't aware that competing AWS and Azure products would only interface with on premise data sources. I haven't dove deep into these limitations as provided by AWS and Azure, but at the same time, my light initial research has led me to believe that data could be moved from on premise environments into AWS and Azure products for the purpose of being consumed by Redshift or Synapse. I would image you are quite busy, but it would be pretty awesome if you could expound on that particular limitation of Redshift and Synapse as it pertains to these products being behind Snowflake in this regard.
Great article!
Hi Owen, Thank you for the comment. AWS and Azure have the ability to do database migration projects (similar to Snowflake) and be consumed by their own data warehouse products. Where Snowflake differentiates itself, is that it can connect AWS and Azure cloud storage, while AWS and Azure are not compatible with each other. This creates the problem of data silos as most companies have data in both AWS and Azure and the data cannot connect together. I hope this clarifies it.
I liked your statistics "% of customers using data sharing." That is a good metric. Also compelling that you have have first hand experience with a data migration to Snowflake! 👍