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Snowflake: Migrating to the Cloud

MMS Founder
MMS Raul Salas

The main driving factor in migrating to the cloud is cost of ownership and ability to scale a database environment rapidly and with no impact to an application. Cloud databases will address many of these driving factors. Many businesses today are planning to move their databases to the cloud.

In recent months, this push has been accelerating. Of the current cloud based data warehouses on the market, Snowflake has been the first choice for many business aiming to make this transition, and for good reason.

One of the most prominent advantages of Snowflake is that tuning and indexes are not needed, especially when dealing with relational queries against structured data. In addition, scaling can be done without disruption, whether it’s up or down. Database management is done automatically and there is unlimited query concurrency. The built in high availability and 90 day data retention protects against node failures, human errors, unforeseen events, and malicious attacks.

The IDC predicts that by 2023, 50% of revenue for data and analytics will come from public clouds, representing a 29.7% compound annual growth rate. This means pubic cloud deployments are projected to grow eight times faster than onpremises deployments which sits at 3.7%. Gartner projects and even more aggressive switch to the cloud than IDC, predicting 75% of all databases will be deployed or migrated to a cloud platform by 2022. Further, Gartner predicts only 5% of these workloads will return to on-premises deployments.

The ability of Snowflake to scale so easily and effectively is partially a function of its architecture. Snowflake does not store data on separate nodes or have the same limitations as on premises SAN storage. Additionally, for storage, Snowflake fully encrypts, and compresses data to bring down costs. It also extracts metadata to enable a more efficient query process with no need for indexing. By retrieving the minimum amount of data needed from storage to run a query, Snowflake can process these requests quicker. Caching data and query results locally results in faster performance with less compute. A consistent view of the data with no blockers can be provided by parallel processing with support from multiple compute engines. In addition, There are multiple AWS availability zones that are composed of stateless compute resources that run across them. This layer provides the unified data presentation layer to include replication and data exchange. In addition, all security functions, management, and query compile operations and optimization as well as coordinating all transactions. In short, cloud databases will be all the rage in 2020 and into 2021, simplicity of management and the ability to scale easily will be significant factors leading management to adopt Snowflake.

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