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Break data silos and have all your data stored in a single place

If you are willing to look for cloud data warehouse solutions beyond those provided by cloud providers Snowflake has a unique approach to save cost.
Evaluate if Snowflake is advantageous to you 

High performing scalable Data warehouse at the right cost for the use case matters. Traditionally data warehouses have been sized by the amount of data stored and the cost was heavily influenced by the data size. Snowflake Architecture brought a paradigm shift in this thinking where it separated the compute from the storage.  

This was possible due to 2 key factors: 

  • Low storage costs offered by the new age cloud vendors such as AWS, Azure and GCP
  • Ability to switch on and scale the compute automatically as per load

 

As a result, you can store as much data as you like and still get charged very less if your usage is low. 

big-data

Break your Data Silos

Avoid lockin with cloud vendor

Leverage 3rd party Data

Snowflake Architecture

The premise of Snowflake Architecture is separation of storage and compute so that each can be scaled separately.
  • What is Snowflake Data Cloud?

Snowflake is designed on top of the cloud computing infrastructure provided by Google, Microsoft Azure, and Amazon Web Services. It’s perfect for enterprises who don’t want to provide resources for setup, maintenance, and support of internal servers because there isn’t any hardware or software to choose, install, configure, or manage. And any ETL or ELT tool may be used to transfer data easily into Snowflake. Snowflake enables data storage, processing, and analytic solutions that are faster, easier to use, and far more flexible than traditional offerings.  

  • Architecture of Snowflake
Snowflake’s architecture is a hybrid of traditional shared-disk and shared-nothing database architectures. Similar to shared-disk architectures, Snowflake uses a central data repository for persisted data that is accessible from all compute nodes in the platform. But similar to shared-nothing architectures, Snowflake processes queries using MPP (massively parallel processing) compute clusters where each node in the cluster stores a portion of the entire data set locally.

Three key layers of Snowflake architecture is as

  • Cloud Services
  • Query Processing
  • Database storage
Our mission is to collaborate with forward-thinking leaders and equip them with the technologies to propel their enterprises to new heights with the strategic use of Data, AI, and Automation.

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