Credit: panumas nikhomkhai
The Snowflake database has become a preferred solution for businesses in recent years.
But what is the Snowflake database?
Snowflake is a cloud-hosted relational database for building data warehouses. It’s built on AWS, Azure, and Google cloud platforms and combines the functionalities of traditional databases with a suite of new and creative capabilities. It is unique in how it addresses businesses’ changing needs.
Building on its Multi-Cluster Shared Data Architecture, Snowflake offers a singular and cohesive data experience. Snowflake data warehousing capabilities are also cloud-based.
Data can be loaded in bulk or in a continuous process into Snowflake.
Data backup is taken care of by the Time travel and Failsafe features of Snowflake. We have control over backup by defining the retention period of database objects or by selecting objects types (Permanent, Transient, or Temporary) depending on the need to reduce storage cost.
If you’re looking to adopt the Snowflake data cloud management solution, this article gives you some features that make the Snowflake database stand out.
Automated Scalability Solutions
With Snowflake cloud services, users of the Snowflake database can increase cloud computing speed and storage separately and often without interrupting services. Compute resources are billed for a minimum of 1 minute in snowflake credits and storage cost is calculated after data compression.
Imagine being a startup with a small virtual warehouse requirement. You can scale up your requirements during peak seasons or busy periods and seamlessly roll back after.
The Snowflake cloud data platform also comes with auto-scaling and auto-suspend features to further reduce the strain from maintenance and administrative work involved in running your cloud infrastructure. Snowflake supports both vertical and horizontal scaling of computing resources.
- Auto-scaling allows the Snowflake platform to automatically open and close compute clusters to adapt to changing requirements, particularly during periods of resource-intensive processing. This feature lets Snowflake DB dynamically manage the workload in your warehouse.
- Auto-suspend automatically switches off a virtual warehouse’s clusters after a predetermined time. Virtual warehouses don’t abort queries even when automatically suspended. Before shutting down, active queries are resolved.(Suspension of the virtual warehouse is handled in a way such that no active queries are affected in the process.) After this, the status becomes “Suspended.”
With the two features above, users can expect rapid scaling, in both directions, without disrupting your operations.
Support for Semi-Structured Snowflake Data
Snowflake boasts one of the most versatile platforms for handling semi-structured data sets among database providers. This hybrid form, which is structured but not necessarily presented in the tabular form common for conventionally structured data sets, has given rise to NoSQL database programming.
This type of data often comes in JSON format, which requires special data pipelines developed specifically to extract attributes from pieces of data and realign them into the required structure.
CSV, TSV, JSON, XML, and PARQUET are some of the data structures that are supported in snowflake.
Data sharing is possible in snowflake between snowflake users and non-snowflake users.
Clone feature in snowflake allows making copies of data without actually incurring additional storage costs. Take a look at our interactive Snowflake pricing calculator.
Result cache, and data cache features of snowflake results in faster retrieval of data along with a reduction in processing cost.
In Snowflake’s proprietary architecture, structured and semi-structured data can be automatically directed to the same destination. This directing is made possible by using a schema on reading data type known as VARIANT.
VARIANT is a Snowflake data type that accepts structured and semi-structured data, which Snowflake automatically parses. The parsed information is prepared for attribute extraction and stored in a recognizable structured data format.
Credit: luis gomes
Snowflake Database Compartmentalization and Concurrency
Snowflake DB uses the multi-clustered shared data architecture to separate its data storage and computation resources. In doing so, Snowflake customers can enjoy faster response time with resources capable of addressing more queries simultaneously.
Traditional databases usually focus on fixing workload, often addressing a specified query type. It means that for more complex applications, as is often the case with real-world requirements, administrators have to set up multiple data warehouse instances. Each of these setups is isolated from the other and is specifically designed to handle a specific workload.
In a Snowflake database, you don’t need to use the same approach, thanks to its development of virtual Snowflake data warehouses. These are small, isolated segments within the larger Snowflake cloud data platform—each performing the function of a conventional data warehouse.
Also, like the conventional multiple data warehouse setup, these virtual warehouses are completely independent of each other.
Imagine having a cloud data warehouse that could detect increasing traffic and implement a real-time response in computing resource allocation or preprogrammed events to trigger pause or temporary shutdown scenarios. With these technologies in place, concurrency and compartmentalization for increased volume and variety of workloads are made easier.
Minimal Maintenance and Administration
At its core, Snowflake is offered as a data warehouse as a service (DWaaS) solution, a more specific solution apart from software as a service (SaaS) or platform as a service (PaaS).
The unique Snowflake architecture means that it is possible to develop solutions, even without imposing heavy dependencies on the client’s database administrators or IT teams. There’s no need to commission software installation or install physical terminals.
The same conveniences apply when you need to scale your project. Increasing the virtual warehouse size or the volume of clusters is made easier and more manageable in real-time. There are even instances where manual server sizing and cluster management are no longer needed.
Also, since Snowflake has enough built-in resources to do away with indexing, you and your teams no longer have to perform your table indexing or database tuning and calibration. All upkeep, such as routine checkups, server maintenance, and software upgrade, is handled by Snowflake and its in-house team.
While Snowflake is not the only DWaaS supplier, its user interface is rarely matched, especially with web browser support. For example, adding the SQL Server Management Studio allows you to access Microsoft Azure Synapse Analytics. It contains a suite of data integrations and Snowflake big data analytics capabilities that give you insights into data in your systems.
Snowflake Data Warehouse Security
From industry-grade security measures across its data banks to allowing your administrators to control personnel access, Snowflake cloud data warehouse employs a comprehensive strategy for data security to keep your confidential business information safe and secure.
It uses SCIM for user identities and compartmentalized roles, automating the exchange and verification of each user’s information between IT systems and identity domains.
All Snowflake editions, such as Business Critical and Enterprise, are equipped with industry standards regarding the site and network access, complete with VPC/VNet communication and the Snowflake service. It even offers security features from simple session timeout configuration to key pair rotation, meeting many cybersecurity demands.
Lastly, its security capabilities can be summarized by compliance with local and international standards. It has full compliance for Soc 1 Type II and Soc 2 Type II. Also, the platform’s Business Critical Edition supports HIPAA requirements and PCI DSS, Moderate FedRAMP, and IRAP Protection, to name a few.
In choosing a database solution for your business, find what suits your unique needs. By understanding what makes companies choose Snowflake DB over other DWaas, you can also make informed decisions for your database provider.
If you decide to get started with Snowflake, enlist the services of a professional team.
Contact us today and make the most out of your database adoption strategies.