Why Snowflake is a Top Cloud Data Warehousing Solution - Debi Prasad Mishra
Why Snowflake momentum as top cloud data warehousing solution now a days.
Audiences: This would be helpful who are learning or trying to build a career in Snowflake. Every explanation here talks about Five Thousand feet top view of Snowflake Product usage and its internal characteristics.
Credits: Snowflake Inc.
What is Snowflake: One of the most popular data platforms which operates as a cloud data warehouse solutions and has the ability to support multi-cloud infrastructure environments. Otherwise Snowflake is known as the data cloud system built on top of cloud service infrastructures such as AWS/ Azure/ GCP which allows the storage, compute and to scale independently. Snowflake is a fully managed SaaS i.e. software as a service by model.
Data Platform as a Cloud Service: All components of Snowflake running on public cloud infrastructure completely and can’t be run on private clouds such as on-premises or hosted. It’s not a packaged software nor installed by users & managing all sorts of software installation and updates. Thus the beauty is:
There is no hardware to select, install, configure, or manage.
There is virtually no software to install, configure, or manage.
Ongoing maintenance, upgrades and tuning are handled by Snowflake.
Top 20 Reasons making Snowflake As Unique
01- Snowflake is a unique product in the market by its own architecture which provides a single platform for data warehouse, data lake, data engineering, data science, data application development, secure sharing and consumption of real-time / shared data analysis under one umbrella.
02- One of the major selling point of Snowflake is separation of data storage compute resources and cloud services in cloud architecture. The best part is the cost is associated with Snowflake based on the usage of each layers and their functionalities independently.
03- Pay per use pricing model meaning that you will only pay based on the amount of data you store and the compute hours/minutes you use. Unlike a traditional data warehouse, Snowflake also gives the flexibility to easily set-up the idle time so you don’t need to pay if the warehouse is inactive.
04- Snowflake offer role based access control mechanism of authorization in securities to grant/deny. Ensures user access only information they need and prevents them from accessing information doesn’t need and benefits are improving in operational efficiency, enhancing compliances & reducing cost.
05- Snowflake brings an extraordinary power of flexibility & scalability that enables memory, temporary storage, to perform various operations as query execution, data loading, unloading and data manipulation operations etc. by virtual warehouse which is one/more no of clusters of compute resources.
06- Snowflake supports two ways to scale warehouses. Scaling up for large workloads is increasing the compute power of the existing warehouse node helps assisting long run query and query that requires a lot of bytes scanned. Scaling out for concurrency is adding clusters to multi-clusters to an existing warehouse. Helps assist when there is a large no of concurrent queries being executed in same warehouse. Scaling Out most favorable for queued queries.
07- Snowflake offers data sharing concept as a single copy of data & shared secured anywhere that eliminates cross-cloud and cross-region replications. With a single copy of shared data, teams across ecosystem can be rest assure they are working from a single source of truth.
08- Snowflake marketplace discover, evaluate and purchase data services & the applications you need to innovate for your business. It helps reducing the integration costs with third party and accessing fresh/live data avoiding the risk and hassle of copying and moving stale data.
09- Zero-copy cloning that makes a copy of a database without duplicating the data it contains. The clone operation takes a snapshot of the source data when the clone is created, and makes this data available to the cloned object.
Advantage is making many data copies without additional storage expenses.
10- Snowflake time travel allows you to access historical data at any point of time. A very effective tool for the tasks such as restoring tables, schemas and databases that may have been removed by accidentally or on purpose. Helps backing up data from previous periods, analyzing over a set period of time.
11- Snowflake offers column-level security feature that uses masking policies to selectively mask data at query time that was previously loaded in plain-text into Snowflake is known as dynamic data masking. Key benefits are easy to use and write a policy once and have it apply on multiple columns.
12- Similarly row access policy can be implemented for row-level security to determine which rows are visible in the query result at run time. A row access policy is a schema-level object include a mapping table in the policy definition to determine whether a given row can be viewed from SQL statements.
13- A critical part of Snowflake is the storage of data and capable of storing data both within the environment and accessing data that is stored in other cloud storage environments. The location the data is stored in is known as a stage whether data is stored internally or externally. Automatically created and managed by Snowflake itself.
14- Snowflake enables loading data from files as soon as they’re available in a stage location which is auto ingest facility using snowpipe. This can load data from the files in micro-batches and making it available to users within minute, rather manually executing the copy command on a schedule to load batches.
15- Stream is an object that records the delta information for a table such as staging table including inserts and other dml changes as well. Stream allows querying and consuming a set of changes to a table at the row level between two transactional points of time.
16- Snowflake task defines a recurring schedule to execute SQL statements including the statement that call a stored procedures and can be linked with together for successive execution to support complex periodic processing.
17- Snowflake’s architecture makes it possible to query semi-structured data and structured data together using SQL. You can join, window, compare, and calculate structured and semi-structured data in a single query. Thus it is for all forms of data in Snowflake.
18- Data coming from various sources, applications, sensors, mobile devices, etc. To support these diverse data sources data formats become so popular to read and store data. There are built in file format objects to support import & export. Supported formats json, avro, orc, parquet and xml. Provides native data types array, object and variant for data storing in data base.
19- Snowflake provides programming languages such as Go, C, Java, .NET, Python, Node.js, etc. For general users provides complete ANSI SQL language support for managing day-to-day operations.
20- Supports many data integration & analytical tool and works seamlessly in Snowflake.
21- By default, Snowflake applies security & encryption customer data at no additional cost. End-to-end encryption allows a customer and to read the data in runtime, that the cloud storage only stores the encrypted version because a user encrypts stored data before loading it into Snowflake.
22- Snowflake offers user-friendly UX for users with & without programming experience. ANSI SQL language is used to support general users.
Conclusion: Snowflake was born from the idea of bringing the capabilities of a traditional data warehouse/lake while at the same time enabling elasticity & scalability of the cloud without worrying about things like costs, performance, or complexity of the system. Thus all above mentioned capabilities, can build your own data architecture within a single platform. Snowflake has been designed for organizations of all sizes to efficiently make use of vast volume of data from all varieties of sources with a minimal cost.