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Snowflake vs Teradata

To anyone with even a passing level of familiarity of this space, Teradata is quite rightly known as a powerhouse in the data warehousing and analytics arena. it's been the go-to technology for sectors ranging from various 3 letter intelligence agencies, to the most recognizable of medicine, science, auto, and telecom industry players combined.

We have been building data systems for years, including those incorporating Teradata (such as for a Data Warehousing project we executed for TicketMaster back in 2007), so this really is the most excited we've been in all that time, given all the new capabilities available now, as compared to then. Today we wanted to share with you some findings based on several industry-leading reports concerning cloud data warehousing and analytics in 2017/18, especially as it concerns Snowflake when compared to such an industry giant such as Teradata.

Sometimes being an industry leader, with a long history in a given space, doesn't always redound to one's benefit, especially given the speed with which advancements tend to be made in these technologies. Newer, smaller upstarts can more easily leap-frog ahead with services that extend beyond those of existing stalwarts, given the right approach. That's essentially what appears to have happened with a company called Snowflake. Here's what a recent Gartner comparison reveals between the two: https://www.gartner.com/reviews/market/data-warehouse-solutions/compare/snowflake-computing-vs-teradata

As can be seen from that list, basically every single category is rated higher, significantly higher, or (in rarer cases) simply even, with Snowflake than with Teradata!

Another emergent technology research and analysis firm, GigaOm, recently released a study called "Sector Roadmap: Cloud Analytic Databases 2017". In it, they identify six "Disruption Vectors" that best determine the viability of any cloud analytic database platform moving forward. The six vectors identified being:

• Robustness of SQL
• Built-in optimization
• On-the-fly elasticity
• Dynamic Environment Adaption
• Separation of compute from storage
• Support for diverse data

The results?

Considering how Teradata's storage pricing ranges from a minimum of $3,000 per TB of data, all the way up to $50,000 per TB (https://www.teradata.com/Resources/Brochures/Teradata-Workload-Specific-Platform-Pricing/) one just has to glance at the seismic difference in price on offer from Snowflake to see how monumental the savings - and benefits - truly are... With an on-demand price of just $40/TB per Month, or a pre-paid price of only $23/TB per Month, the savings, over Teradata, stack into the thousands per month on storage costs alone. Compute is scaled completely automatically as well, so the power is there, without wasting it when it's not needed. The difference in expenditure required is simply astounding!

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