13 Key Snowflake Features: Traits that Take It to the Top

13 Key Snowflake Features: Traits that Take It to the Top

Snowflake's Cloud Data platform is one of the most sought-after tools by companies that wish to upgrade to a contemporary data architecture. Snowflake stands out from the rest of cloud data warehouse solutions as an integrated service platform because of a few unique features. Well, let's have a look at those remarkable traits at a glance.
21 Dec 2022
Sumi S

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    A Compact List of Snowflake Features

    1. Decoupling of storage and compute in Snowflake
    2. Auto-Resume, Auto-Suspend, Auto-Scale
    3. Workload Separation and Concurrency
    4. Snowflake Administration
    5. Cloud Agnostic
    6. Semi-structured Data Storage
    7. Data Exchange
    8. Time Travel
    9. Cloning
    10. Snowpark
    11. Snowsight
    12. Security Features
    13. Snowflake Pricing

    Let’s deep-dive:

    1. Decoupling of storage and compute in Snowflake

    Snowflake’s decoupling of storage and compute features facilitates virtual warehouses and storage as separate entities. Leveraging this functionality of Snowflake, businesses can achieve greater flexibility in choosing the compute of their choice and incrementally pay for what they store and compute. Users can scale up / down or in/out based on the business SLA requirement. Scale up – Scale-out features do not require downtime and are almost instant.

    2. Auto-Resume, Auto-Suspend, Auto-Scale

    Snowflake’s auto-resume and auto-suspend features provide minimal administration. Using auto-resume, Snowflake starts a compute cluster when a query is triggered and suspends compute clusters after a set time of inactivity. These two features ensure performance optimisation, cost management, and flexibility.

    In business circumstances where more users are querying heterogeneous queries, setting up auto-scaling can help automatically expand the number of clusters from 1 to 10 at an increment of 1 based on the volume of queries sent to a compute simultaneously.

    3. Workload Separation and Concurrency

    Concurrency is no longer a problem for Snowflake, unlike traditional data warehouses with concurrency issues where users and processes must compete for resources. Because of Snowflake’s multi-cluster architecture, concurrency is not an issue anymore.

    This architecture also helps to divide workloads into their virtual warehouse and channel the traffic to each virtual warehouse (compute) by functions or departments.

    4. Snowflake Administration

    A data cloud as a service is provided by Snowflake (DWaas). Businesses can set up and administer a system without significant assistance from DBA or IT teams. Unlike the on-premise platforms, neither hardware commissioning nor software installation patch-update is s necessary. Snowflake manages software updates and introduces new functions and patches without downtime.

    Snowflake automatically creates micro-partitioning. This feature reduces the requirement of manually indexing and clustering tables though these are available features in Snowflake.

    5. Cloud Agnostic

    Being a cloud-agnostic platform, Snowflake can migrate its workloads with other cloud providers. So, Snowflake is accessible on all three cloud providers: AWS, Azure, and GCP. Customers can easily integrate Snowflake into their existing cloud architecture and choose to deploy in locations preferred by their companies.

    6. Semi-structured Data Storage

    The requirement to manage semi-structured data, often in JSON format, gave rise to NoSQL database solutions. Data pipelines are created to extract attributes from JSON and mix them with structured data. By leveraging VARIANT, a schema on read data type, Snowflake’s design enables storing structured and semi-structured data in the exact location. Both organised and semi-structured data can be stored using the VARIANT data type. Snowflake eliminates the need for data extraction pipelines by automatically analysing data, extracting properties, and saving it in a columnar format.

    Snowflake can connect to staging areas like s3 bucket, Azure blob or GCP blob storage to retrieve and transform files stored in these platforms. This is regardless of the cloud Snowflake is hosted. A snowflake-managed staging area is also available. Tasks/ Streams or Snowpipe can be set to retrieve data at a scheduled time or almost instantly, respectively. Snowflake can work with CSV, JSON, XML, Avro, ORC, and Parquet file formats. Snowflake can also store metadata of unstructured data stored in the staging area.

    7. Data Exchange

    A wide range of data, data services, and applications are available on the Marketplace. From some of the world’s top data and solution suppliers, you can find, assess, and buy data, data services, and apps through Marketplace. Direct access to data ready for querying and pre-built SaaS connections virtually eliminates the expenses and delays associated with conventional ETL operations and integration. The risk and hassle of duplicating and relocating outdated material should be avoided. Instead, you can receive automatic updates that are close to real-time and have secure access to shared, controlled, and live data.

    8. Time Travel

    One of the distinctive Snowflake elements is time travel. You may follow the evolution of data through time by using time travel. All accounts have access to this Snowflake feature, free and enabled by default for everyone. Additionally, this Snowflake feature allows you to retrieve a Table’s historical data. At any moment throughout the previous 90 days, one can access the table’s appearance.

    Time travel encompasses the undrop feature. If an object has not been removed yet by the system, a dropped object can be recovered using the undrop command in Snowflake. When an object is undropped, it returns to its original condition. The option to undrop schemas or tables is also available.

    9. Cloning

    The clone capability allows us to quickly duplicate anything, including databases, schemas, tables, and other Snowflake objects, in almost real time. Therefore, cloning an object involves editing its metadata rather than duplicating its storage contents. You can quickly produce a clone of the whole production database for testing purposes.

    10. Snowpark

    With the help of the Snowpark feature, data scientists and data engineers proficient in Python, Scala, R, and Java may create and manage their codes in Snowflake. Snowpark helps to employ the computing capabilities of Snowflake to retrieve, transform, train and apply data science models on the data stored in Snowflake, which has a more apparent performance advantage,

    11. Snowsight

    The new Snowflake web user interface, Snowsight, replaces the traditional Snowflake SQL Worksheet and enables you to easily construct basic charts and dashboards that can be shared or explored by many users, do data validation while loading data and conduct ad-hoc data analysis. The Snowflake dashboards tool is an excellent option because it works well for individuals or small group users in an organisation who wish to generate straightforward visualisations and share information among themselves.

    12. Security Features

    Snowflake assures security for its users through the following methods:

    • • By adding IP addresses to a whitelist, you may control network policies and limit who can access your account.
    • • By supporting several authentication techniques, including federated authentication and two-factor authentication for SSO.
    • • Using a hybrid approach of role-based access control and discretionary access control. In role-based access control, privileges are assigned to roles which are then transferred to users. Still, in discretionary access control, each object in the account has an owner who controls access to the object. This hybrid strategy offers a substantial level of flexibility and control.

    AES 256 strong encryption is used to automatically encrypt all data, both in transit and at rest.

    13. Snowflake Pricing

    The advantages of Snowflake pricing are:

    • • Pay for actual consumption only.
    • • We can cut back on resource use to save costs.
    • • Flexible payment. We can either pay on-demand or in advance (pre-purchased).
    • • Scale up or down the use of cloud services, computing, and data storage automatically based on your needs.
    • • There are no chances of overbuying or overprovisioning.
    • Optimisation of Snowflake spending through integration with innovative cost-monitoring platforms.

      Snowflake stands as an ideal and popular choice because of its unique and updated features. It is also available across many data cloud providers and regions, making it accessible and suitable for all organisations. Why wait? Let’s experience Snowflake. Try now: https://beinex.com/snowflake/.

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