In the current era of Living, we see that the organization holds large volumes of data. Managing large volumes of data has become a tedious job these days. The organizations are looking forward to the best data warehouse platforms to achieve their objectives and goals efficiently. Many data warehousing platforms are available in the market. However, Snowflake has got its own reputation for its unique features, which help organizations and their users reach success in a short span of time. Snowflake is called a cloud-based data warehouse platform that is explicitly built on the top of Amazon Web Services or AWS. Snowflake cloud data warehousing platform is said to be a software as a service offering. In this tutorial, you will gain an understanding of Snowflake, its architecture, advantages and many more. You will also gain an understanding of the different features which make Snowflake a leader in the market. Let's get started.
What is a Snowflake data warehouse?
A snowflake data warehouse is referred to as the data storage and analytic service, which is built on the cloud, Unlike the other data warehouses. Snowflake allows businesses or organizations to analyze and store the data by using cloud-based tools. It is called the first analytics service designed to run on different providers like Google Cloud platforms, Azure, AWS, etc.
The snowflake data warehouse does not require any hardware or software installed or managed or configured and completely based on the cloud-based infrastructure. Snowflake service is ideal for developing their applications, data science, data engineering, data warehouse and many more. Snowflake is called the fastest-growing application because of its unique features, allowing it to analyze the data quickly. Snowflake has developed features and architecture, including data sharing facilities and virtual data warehouses, to manage large volumes of workload in day-to-day operations.
Snowflake is a platform that allows the data storage and passing along with the analytics of the data in a faster and flexible way when compared to the other traditional offerings that are available in the market. The snowflake data warehouse on the data platform is not specifically built on the existing database Technology but also is flexible to combine with a completely new SQL Query engine. Snowflake is one platform that provides users with all the functionalities required for an enterprise analytic database and some unique capabilities and flexibilities.
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Why is Snowflake unique?
When compared with The Other traditional data warehouses, Snowflake is known for its cloud cloud-based data warehouse, which includes the separation of the compute layer and storage layer, which will also allow each of them to be scaled independently within the given reasonable or cost-effective price. In Snowflake, you will be paying only for the capacity and the performance that you use. Most of the other traditional or different data warehouses will also process the same features; however, Snowflake customers have given a better review stating that they have chosen Snowflake for its scalability, which is one of the essential features.
Let us have a brief understanding of the architecture of Snowflake and how it works.
Architecture of Snowflake
As mentioned earlier, Snowflake is built on the cloud, which has come up with a unique multi-clustered shared architecture. As every organization looks for the features like high performance, elasticity and concurrency, Snowflake is found to be the best among the data warehouses available in the market. It is flexible to provide all different activities like resource management, data protection, availability, authentication, etc. Snowflake includes the compute, storage and global service layers, which are logically integrated but are physically integrated.
Snowflake makes use of the shared disk architectures, which utilize multiple nodes for accessing the shared data on a single system. The shared architecture follows the process of sharing the part of the data in each data warehouse node. Snowflake can process the queries using the massively parallel processing computer clusters in which every node in the cluster will store some part of the entire data set locally.
Snowflake Data warehouse consists of three different layers in the snowflake architecture. They are:
1. Database storage
2. Query processing
3. Cloud services
Let me give you a brief explanation of each layer in the snowflake architecture.
1. Database storage: All the data is stored in the database in Snowflake. A database is referred to as the grouping of the objects logically, consisting of the tables and views that can be further classified into one or more schemas. The Snowflake allows storing any kind of data, which can be either structured or unstructured data, and stores all the tasks related to the data, which are handled through the SQL query operations. Snowflake is responsible for managing all the activities on how the data is stored. It makes sure that Snowflake completely handles the file structure, compression, statistics, and other aspects of the data storage.
2. Query processing: In this layer of query processing, Snowflake is responsible for processing the queries using CS, which makes use of the virtual warehouse consisting of the data that is present in the storage layer. They will be separately run to not share or complete the data warehouses with the other resources. Virtual warehouses are specifically used to run queries and data loading and also provides it support and flexibility to perform both of these tasks simultaneously. A virtual warehouse is allowed to be scaled up or down.
3. Cloud services: The Cloud Service layer is responsible for coordinating in handling the services in Snowflake, including encryption, SQL compilation, sessions, etc. It is also responsible for eliminating or removing the manual data warehousing and tuning requirements. Below is a list of services that are included in the Cloud Service layer.
2. Infrastructure management
3. Metadata management
4. Query parsing and Optimisation
5. Access control
All the services and layers are independently scaled and redundant with each other. To understand better how the different layers work together you need to have an idea about the life cycle of a query.
Once the Snowflake is connected using any one of the supported clients and the session is started, then the first virtual warehouse will submit a query. The service here will verify if this is unauthorized access or not in the database. Once authentication is done, it will execute the operations defined in the query and create an optimized query plan. The next step is with a service layer that will send the query execution instructions to the virtual warehouse and is responsible for allocating the resources. This is because any data from the storage layer will be responsible for executing the query. All the results obtained will be then returned to the user.
Along with unique architecture, Snowflake has come up with extensible features that have improved demand for the platform in a short span of time. I will give you a briefing about the different features available in Snowflake.
1. Availability: The snowflake architecture is designed to support the fully distributed and plans across the globe in the different availability zones and regions. Snowflake is also highly faulted tolerant to the failures that arise in the hardware. The number of users who face issues or notice the impact of the failures in the hardware is very less.
2. Security: security is one of the important aspects of Snowflake architecture. In the snowflake architecture, data encryption takes place when the data is in transit and rest as well. Snowflake utilizes different authentication mechanisms that include federated authentication with support for single sign-on access and also two-factor authentication. The security feature in Snowflake includes role-based access control so that it provides the authenticated users to access the data rather than everyone. It has come up with the capabilities to restrict the users based on the predefined criteria. Snowflake is also compatible to work with the host of certifications like socl2 type 2 and also HIPAA.
3. Multi-cloud: Snowflake the only latest platform, Unlike the traditional offerings that are available in multiple clouds with the best User experience and keeping up the value of customers. Snowflake allows its users to be more comfortable using the clouds as and when required. It also helps in reducing the moving data back and forth from the cloud environment to Snowflake using the internet. Snowflake is available on different environments of platforms like Microsoft Azure, Google Cloud and Amazon Web Services.
4. Pricing: Snowflake offers the best pricing, which is reasonable and simplified, providing a positive experience to the users. Users will be allowed to pay only for the stories they use and the computing power deployed to process the request. There will not be any sort of class involved or extensive planning required to start with the data warehouse initiation. Snowflake architecture includes clusters that automatically help process the work clothes and scale down to the predefined size. Uses will be built based on the usage of capacity that they are actually used and also for the expanded capacity based on the duration.
5. Scalability and performance: As per the latest update, we see that there is a high demand for Snowflake for the performance capability and scalability that holds. As Snowflake follows architecture in which compute and storage are separately treated, Snowflake has paved the way to minimize or eliminate the bottleneck that is associated with the Other Technologies, specifically the traditional offerings. Users will be allowed to start by providing the cluster size for initial deployment and will also be allowed to scale as and when required when the system is up and running. Snowflake will handle the scaling operations transparently.
6. Near Zero administration: Snowflake is flexible in removing the management constraints and is a cloud-native data warehousing platform. Snowflake is designed in such a way that the performance level will be represented at a high level and will also lead to the elimination of the administration overhead. Based on the demands of the workload, the database will be managed entirely and scale automatically. Snowflake also includes the capability to build performance tuning, Optimisation capabilities, and infrastructure management, which will help the business live in peace. The only thing that needs to be done is to bring the data and leave the data and its management to Snowflake.
Collaboration and sharing:
snowflake has come up with one of the essential features, which are sharing in collaborating with the data owners. It allows the data owners to share the relevant data with the different partners and consumers. There is no need to create a new copy of the data. There is no utilization of storage or data movement, and the consumer will only pay for the processing of the data. It also helps remove the hurdles involved in email or FTP by using the sharing features available in Snowflake.
Connecting to Snowflake:
Snowflake is designed in such a way that it is compatible to be connected with the other services in many different ways. Below are the few sets of options or services to which Snowflake can be connected.
1. Odbc and JDBC drivers
2. Native connectors
3. Command-line clients
4. Third-party characters such as business intelligence tools and ETL tools.
Loading of data in Snowflake:
In the section, you will learn about the fundamentals of loading the data into Snowflake. Snowflake is flexible to support four different options to perform data loading. They are:
1. Snow SQL for bulk loading
2. Snowpipe in order to automate the bulk loading of data
3. Webui for limited data
4. Third-party tools to load the bulk amount of data from external sources.
Let me give you a brief description of each type of loading available supported by Snowflake.
1. Snow SQL for bulk loading:
Firstly we need to know that the bulk loading of data will be performed in two different phases. They are Staging files and loading data.
Staging the files: the first phase of bulk loading of data is Staging files. Staging files usually refers to uploading the data files to a particular location where the Snowflake can be allowed to access. The next step is to load the data from stage files into tables. The Staging of files happens on some internal locations, which are called Stages in Snowflake. In order to provide secure storage of data files without any dependency on the external locations, the internal stages are used.
Loading the data: in order to load the data, a virtual warehouse is required to load the data into Snowflake. The warehouse is responsible for extracting the available data in each file and inserting it in the form of rows in the table.
In the snow SQL type of bulk loading in Snowflake, the CSV files will be loaded from the word local machine into a contact table. The same name will be used in internal Staging to store the files before performing the loading of the data.
2. Snowpipe: Snowpipe can also be used to perform the loading of the data in which this specifically from the files stage in the external locations. Snowpipe makes use of the copy command, which has come up with some additional features and will allow you to automate the process. It also makes use of the external computer resources in order to load the data continuously and also help in eliminating the requirement of a virtual warehouse.
3. Third-party tools: In order to perform the loading of data, third-party tools like ELT can be used. Snowflake provides extensible support to expand the scope of the ecosystem of applications and services in order to load the data from a wide range of external sources.
4. Web interface: The web interface is the only last option that is available for loading the data. In the web interface type of loading, you will need to select the table that you want to choose and then click on the load button. Once you click on the load button, you will be allowed to load a limited amount of data into Snowflake. The web interface type of learning will help in simplifying the loading activity as it combines both the Staging and loading of data into a single operation and is also flexible in removing or deleting the files once the loading is completed
Benefits of Snowflake
Unlike the traditional offerings or the traditional data warehouses, Snowflake is the cloud-based data warehouse that has multiple unique features and benefits. A few of the benefits are listed below:
1. Simple and friendly to use: Snowflake has a simple interface that is easy to understand and allows you to load the data and process the data quickly. It is also flexible and provides support to solve the queries or issues that arise using the exceptional multi-cluster architecture.
2. Data sharing: Snowflake has come up with a unique architecture and includes seamless data sharing required for any customer.
3. Support multiple formats: Snowflake is designed to work or be compatible with multiple formats like JSON, XML, etc. It is flexible to run with any kind of data that can be either structured, semi-structured or unstructured data and help address the issues that arise by handling the incongruent data types that exist, in particular a single data warehouse.
4. Availability of tools: Snowflake is compatible to work with different tools like Power BI, Tableau, etc. It is providing it extensible support by allowing you to run the queries against large sets of data.
5. Scalability: Snowflake has come up with the instant data sharing or data scaling feature, which allows you to handle the concurrency portal next that arises during the period when there is high demand. It allows you to perform the scaling of the data without redistributing the data, which could be one of the interruptions to the end-users.
6. Performance and speed: As Snowflake is a cloud-based data warehouse, if you stick to the cloud's elastic nature, it will allow you to load the data quickly and run the large volumes of data or queries faster. It also provides you with the flexibility to scale the virtual warehouse up and down to take advantage of the benefit of using the extra computer resources and make the payment for that time you have used. Snowflake provides the users with the best outcomes by ensuring that the query processing is taking place at an optimal rate.
7. Flexibility and elasticity: As customer value and customer satisfaction is one of the prominent aspects, Snowflake is making wonders by offering the highest accessibility, elasticity, flexibility, etc. Snowflake specifically allows the user to use both the query services and the warehouse services in the same data lake. Compared with the other offerings available in the market, Snowflake is known for the usage, being said, it is more flexible, and it can be used whenever it is required based on the requirements.
As of 2021, there is a high demand for cloud-based products, cloud data warehouses, which have become more popular based on the customer value and customer satisfaction that they are offering. Snowflake is referred to as one of the effective tools that will help manage the data Over The Other traditional offerings available. Utilizing and implementing Snowflake or incorporating Snowflake into your business can help you improve your business performance and efficiently achieve your goals. I hope the above information has helped you in gaining knowledge of Snowflake.