Snowflake stores a portion of every data set locally within these clusters. On top of this, Snowflake is based entirely around ANSI SQL, so the barrier to entry is extremely low.Ĭompute nodes or clusters within Snowflake are known as individual warehouses. Query processing within Snowflake is tackled using massively parallel processing (MPP) to process queries. One of the unique factors about Snowflake is the fact that it has completely decoupled storage and compute processing layers, making it extremely easy to scale up or down as needed. As a PaaS solution AWS comes with more baggage compared to Snowflake because users have to optimize the platform in order to get the most out of the solution. It’s designed to be a central hub to connect other AWS offerings and even query against a data lake directly in some cases. However, Redshift is a native AWS service that is built to work in unison with other AWS technologies. Similar to Snowflake, Redshift lets users query data using SQL for analysis and reporting purposes. Redshift was actually one of the very first cloud data warehouses to become available on the market, launching officially in 2013. However, whereas Snowflake is a SaaS offering, Redshift is a PaaS (Platform-as-a-Service) solution. Like Snowflake, Redshift is also a cloud-based data warehouse designed to tackle Business Intelligence use cases among other things. What Is Redshift?įunny enough, AWS Redshift was strategically named as a deliberate dig at Oracle since all of Oracle's branding is red. One of the biggest advantages of Snowflake is the fact that it was developed solely for the cloud and that means it comes with none of the operational overhead or conventional baggage that other technologies bring to the table. At the time of writing this article, Snowflake is valued at approximately $78.49 billion. This information is then used to power reports and dashboards so business stakeholders can make key decisions based on relevant insights.įounded in 2012 and launching officially in 2014, Snowflake currently holds the record for the largest software IPO in history. With Snowflake users can easily query data using simple SQL. Once data is loaded into Snowflake, data scientists, engineers, and analysts can use business logic to transform and model that data in a way that makes sense for their company. As a SaaS (Software-as-a-Service) solution, it helps organizations consolidate data from different sources into a central repository for analytics purposes to help solve Business Intelligence use cases. It's not specifically based on any cloud service which means it can run any of the major cloud providers like Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform (GCP). At its core Snowflake is a data platform.
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