Snowflake's Value Explained
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- čas přidán 3. 07. 2024
- In this video I breakdown Snowflake! What it is, what it's not, what it's used for, competitors, and future outlook.
Research:
Great benchmark video from 2018! I prefer this researcher's methodology.
• Cloud Data Warehouse B...
Links:
poplindata.com/data-warehouse...
/ redshift-vs-bigquery-v...
fivetran.com/blog/warehouse-b...
seekingalpha.com/article/4429... - Věda a technologie
Very insightful and valuable. Thanks for sharing this level of explanation (detailed but without getting lost in the weeds) of their technical capabilities. Good job!
Thanks so much! One of my favorite channels currently
Another outstanding video! Thanks again for sharing you hard work in researching as well as actual experience (and your team's) with Snowflake. As you know, it's difficult to understand strengths and weaknesses of software products until you've actually used them, which takes considerable time investment. You've also provided excellent information related to competitors and their features. Great video!
Great explanation! Can you do an in depth explanation like you did with this about Palantir? More from a technology standpoint and how it works from your perspective. I'm learning so much from these videos and about IT.
Thanks bro. Undervalued channel.
Very insightful. To the point !
Nice summary. Thanks.
Great coverage. One small point... SybaseIQ was one of the first commercially available columnar databases. It was phenomenal when it came out, but was a bit ahead of its time, and was not widely adopted.
Good video as always. The architecture of snowflake in my opinion: Operational data (SaaS, DB, APIs, etc...) -> Data warehouse and lakehouse with secure data sharing, data marketplace and cloud (the most important features) then data engineers, data scientist, App developers, among others query snowflake tools that include jobs such as data mining, analytics, dashboards, etc ...
This is a GREAT channel. I use your videos to deepen my understanding of this advanced tech, but it would be helpful if you clarified or explained what some of the acronyms stand for
Thanks! Great video. I know Snowflake and Palantir are not really comparable or in direct competition. They‘re rather complementary. At least that’s what I took from your videos here and on beyond our money. In terms of investing and ROI, my longtime bet is on PLTR however.
What data modeling method do you use for this database: 3nf, dim, data vault,?
amazing video for non-tech ppl just like me! Two questions here:
1. do you think SNOW can grow its revenue at a high speed for the next 3 years?
2. for PLTR, I think the biggest issue is that PLTR is not a standardized product as it requires a full team to help its client implement the system (that's what i heard), and it issues too many stock options
Thank you!
1. No, and neither do analysts. That's one of the major reasons the stock tanked. They updated their guidance forecasting decelerating growth. Not financial advice, just my two cents. Do your own due diligence.
2. In my experience Foundry doe not require a "full teams" of consultants. It delivers value on day zero. In my Foundry in Action series we spent ~6 hours on it and had data analyzed in Quiver. I'd say the biggest obstacles center around security and data ingestion. PLTR is a security first company, so some data sources are more complicated to connect to than others. That said if you are a fairly good engineer this shouldn't be an issue as the documentation is good. The most common thing non-technical customers might need help with is connecting data sources (just my opinion). However that would likely be a limited support agreement with a single resource assigned. I also don't see that as out of the ordinary for integration of any service of even mild complexity. Data and storage integration is probably one of the most common issues AWS customers have for example.
Snowflake has recently announced Streamlit acquisition. This will be good complementary for AI/ML comunity. Their customers dont need to DO-It-yourself ML/AI stack hence reducing failure rate from 87%
very neutral view. I liked it.
I am interested in know how a company like Snowflake (and also Palantir) can innovate in order to decrease the 87% failure rate of AI/ML initiatives... seems like a very important challenge to overcome
It's a risk for sure. But that's a selling point for PLTR IMO since their customers are not failing at that rate. The better is question is how people plan to compete with PLTR's customers.
If you want orders of magnitude faster performance on heavy data sets in high tbs or petabytes- its Vertica all day long. Pity they didnt build a managed service and keep pace- the performance today is still unrivalled
Thank you so much, this is easier to understand than what Snowflakes marketing team puts out, LOL
Hmm, then what makes them have 114% growth rate? Simply bcoz base is smaller?
I think so. Also, most of the data engineers I know prefer Snowflake because it's SQL everything and an all in one solution. It handles more corner cases as well than say Redshift.
why do companies need warehousing anyway?
sorry, but snowflake is from 2017
Snowflake started in 2012
Thanks for another great video. On a side note, I'm interested seeing what comes out of Snowflake's recent partnership with C3.ai. Time will tell...