Snowflake’s Data Cloud is powered by an advanced data platform provided as Software-as-a-Service (SaaS). Snowflake enables data storage, processing, and analytic solutions that are faster, easier to use, and far more flexible than traditional offerings.
The Snowflake data platform is not built on any existing database technology or “big data” software platforms such as Hadoop. Instead, Snowflake combines a completely new SQL query engine with an innovative architecture natively designed for the cloud. To the user, Snowflake provides all of the functionality of an enterprise analytic database, along with many additional special features and unique capabilities.
Snowflake is a true SaaS offering. More specifically:
- There is no hardware (virtual or physical) to select, install, configure, or manage.
- There is virtually no software to install, configure, or manage.
- Ongoing maintenance, management, upgrades, and tuning are handled by Snowflake.
- Snowflake runs completely on cloud infrastructure. All components of Snowflake’s service (other than optional command line clients, drivers, and connectors), run in public cloud infrastructures.
- Snowflake uses virtual compute instances for its compute needs and a storage service for persistent storage of data. Snowflake cannot be run on private cloud infrastructures (on-premises or hosted).
- Snowflake is not a packaged software offering that can be installed by a user. Snowflake manages all aspects of software installation and updates.
Six Features That Make Snowflake A Different Cloud Data Warehouse:
Cloud Provider Agnostic
Snowflake is a cloud agnostic solution. It is a managed data warehouse solution that is available on all three cloud providers: AWS, Azure and GCP, while retaining the same end user experience. Customers can easily fit Snowflake into their current cloud architecture and have options to deploy in regions that makes sense for the business.
Scalability
Snowflakes multi-cluster shared data architecture separates out the compute and storage resources. This strategy enables users the ability to scale up resources when they need large amounts of data to be loaded faster, and scale back down when the process is finished without any interruption to service. Customers can start with an extra-small virtual warehouse and scale up and down as needed.
To ensure minimal administration, Snowflake has implemented auto-scaling and auto suspend features. Auto-scaling enables Snowflake to automatically start and stop clusters during unpredictable resource intensive processing. Auto-suspend, on the other hand, stops the virtual warehouse when clusters have been sitting idle for a defined period. These two concepts provide flexibility, performance optimization, as well as cost management.
Concurrency and Workload Separation
In a traditional data warehouse solution, users and processes would compete for resources resulting in concurrency issues. Hence the need for running ETL/ELT jobs in the middle of the night when no one is running reports. With Snowflake’s multi-cluster architecture, concurrency is no longer an issue. One of the key benefits of this architecture is separating out workloads to be executed against its own compute clusters called a virtual warehouse. Queries from one virtual warehouse will never affect queries from another. Having dedicated virtual warehouses to users and applications provides the possibility to run ETL/ELT processing, data analysis operations and reports without competing for resources.
Near-Zero Administration
Snowflake is delivered as a Data Warehouse as a service (DWaas). It enables companies to setup and manage a solution without significant involvement from DBA or IT teams. It does not require software to be installed or hardware to be commissioned. With modern features such as auto scaling, both increasing the virtual warehouse size as well as increasing clusters, gone are the days for server size and cluster management. Since Snowflake supports no indexes there is no need for tuning the database or indexing the tables. Software updates are handled by Snowflake and new features and patches are deployed with zero downtime.
Semi-Structured Data
The rise of NoSQL database solutions came from a need to handle semi structured data, typically in JSON format. To parse JSON, data pipelines needed to be developed to extract attributes and combine those attributes with structured data. Snowflake’s architecture allows the storage of structured and semi structured data in the same destination by utilizing a schema on read data type called VARIANT. The VARIANT data type can store both structured and semi structured data. As data gets loaded, Snowflake automatically parses the data and extracts the attributes and stores it in a columnar format. Hence eliminating the need for data extraction pipelines.
Security
From the way users access Snowflake to how data is stored, Snowflake has a wide array of security features. You can manage network polices by whitelisting IP addresses to restrict access to your account. Snowflake supports various authentication methods including two-factor authentication and support for SSO through federated authentication. Access to objects in the account is controlled through a hybrid model of discretionary access control (each object has an owner who grants access to the object) and role-based access control (privileges assigned to roles which are then assigned to users). This hybrid approach provides significant amount of control and flexibility. All data is automatically encrypted using AES 256 strong encryption and is encrypted in transit as well as at rest.
These are not the only reasons why Snowflake is different. There are other features that standout, however these are the ones we have seen our clients benefit from the most. Snowflake should be considered as a solution for any business migrating to a cloud Data Warehouse. One Six Solutions is a Snowflake partner and has implemented Snowflake Cloud Data Platform solutions for clients looking for a modern data architecture platform.
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