What Is Snowflake? Pros and Cons of the Prominent Data Warehouse

Today, companies are facing a continual need to store tremendous volumes of data. The demand for information repositories enabling business intelligence and analytics is growing exponentially, giving birth to cloud solutions. The ultimate need for vast storage spaces manifests in data warehouses: specialized systems that aggregate data coming from numerous sources for centralized management and consistency.

With a wealth of such cloud solutions available on the modern market, Snowflake stands apart as a new approach to storing information. So, what is the Snowflake data platform all about? Its architecture allows companies to perform efficient data management by scaling data storage and making computing tasks separate, saving significant costs. Furthermore, Snowflake’s data sharing capabilities enable users to share and manage secure data quickly in real time. 

The solution became recognized worldwide in no time, and Snowflake gained more than 8,900 clients by 2023.

How does Snowflake work, what makes it so unique, and are there any caveats to it?

In this article, we will answer the question: “What is Snowflake?”, consider its pros and cons, and explain how to employ it efficiently.

The platform enables quick, flexible, and convenient options for storing, processing, and analyzing data. The solution was built on top of Amazon Web Services and is now available on Google Cloud and Microsoft Azure. Therefore, the tool is referred to as cloud-agnostic. This service consists of three layers: Database Storage, Processing, and Cloud Services. The first one, the Data Storage layer, is responsible for reliable and elastic data storage. This characteristic is provided by the cloud platforms on which this solution is based. The data can be accessed through the Processing layer, where scaling a virtual cluster or creating a new one takes only up to five minutes. As for the Cloud Services layer, it’s used to manage data—here, you can create databases, tables, users, and roles.

So, what does Snowflake do? Essentially, it enables you to:

• Store your data in rapid, high-performance data storage
• Avoid the need to obtain new hardware and software
• Entrust all support and updating activities to the Snowflake team

In fact, there are many well-known cloud data warehouses, but, unlike most of them, Snowflake eliminates the need to add virtual servers when scaling. Thus, since there is no forced data redistribution during the scaling process, Snowflake eliminates downtime. This advantage is ensured by the fact that this service is based on a high-performance DBMS that supports standard SQL and complies with ACID requirements.

Snowflake allows for quick recovery of recently deleted objects, usually within 24 hours. To recover objects deleted longer ago, consider Snowflake Enterprise Edition. You can also view recent query results without a virtual cluster and efficiently process semi-structured data like JSON and Avro. These advantages make Snowflake a top choice in the Data Warehouse as a Service market.

Also, to answer the question, “What is Snowflake data platform and what is the technology behind it?”, you can perceive it as a part of the modern data pipeline:

By using the technology, companies can significantly enhance their data management. Thus, the solution allows for scaling data workloads independently from one another and seamlessly handling data warehousing, data lakes, data sharing, and engineering.

Pros and Cons of a Snowflake Data Warehouse

We’ve already explained the Snowflake term, and now we’re going to guide you through its fundamental advantages and drawbacks to provide you with a closer look at the solution.

Snowflake Pros

Extensive Storage Opportunities

Snowflake cloud data warehouse provides affordability, scalability, and a user-friendly interface. The tool’s high storage capacity is perfect for keeping large information volumes.

Multi-cloud Options

You can host the Snowflake data cloud on numerous popular cloud platforms, including Microsoft Azure, Google Cloud, and Amazon Web Services. Such hosting options make the Snowflake cloud an excellent data warehouse solution for organizations in multiple industries.

High server Capacity

Traditional information storage tools typically require significant investment in servers and other related hardware. Snowflake virtual warehouses deliver greater capacity without the need for any additional equipment. The technology is completely cloud-based, meaning you can implement it to the extent you need with further scaling up or down.

Superior Data Security

Companies often deal with sensitive information that needs reliable protection. Snowflake technology provides IP whitelisting to restrict access to data to authorized users. With techniques such as two-factor authentication, SSO authentication, and AES 256 encryption, Snowflake ensures solid data security.

Performance Adjustment

Snowflake features a user-friendly design allowing customers to arrange and quickly query data conveniently. Once adjusted to your needs, this responsive platform can perform optimally without human interference. Of course, this is not a unique quality, but it’s worth noting that Snowflake makes the possibility of customization a priority, and few other solutions can provide such a high level of it.

Disaster Recovery

Traditionally, users may feel safer with physical access to the server in case of failure. However, with the Snowflake DB, customers don’t need to worry about questions like, “Where is the data stored?” Although the databases are kept in the cloud, the solution carries contingencies for disaster recovery. It establishes numerous data centers that copy your data and guarantee easy access in unforeseen situations.

Adjustable Performance

Every business may have fluctuations in its activities. Thus, there are periods of extensive network use as well as lower workloads. With the help of multi-cluster warehouses, available in Snowflake Enterprise Edition, organizations can effectively deal with both rush times and slowdowns, since they ensure scalability upon demand. Therefore, companies can seamlessly accommodate all the changes in user numbers.

Support of Different Data Types 

Snowflake manages structured, semi-structured, and unstructured data. Specifically, it allows users to access this data securely, share access to it with others, and process this data.

Efficient Data Organization

Snowflake’s unique architecture, featuring micro-partitions and automatic data clustering, delivers exceptional performance and efficiency. Micro-partitions enable Snowflake to store data in small, manageable chunks, allowing for independent processing and optimized query performance. Automatic clustering further enhances this by intelligently organizing data based on access patterns, minimizing the amount of data scanned during queries. This combination results in faster query execution, reduced latency, and improved overall performance, especially for complex analytical workloads. Furthermore, this efficient data organization contributes to cost optimization by minimizing the compute resources required for processing queries.

Snowflake Cons

Despite having convincing benefits, Snowflake warehouses do bring about a few downsides. However, this doesn’t prevent the tool from being a primary data warehouse for many users. 

High On-demand Prices

While this pricing model is very transparent, for some usage patterns you may find cheaper alternatives, such as Amazon Redshift. At the same time, it’s easy to calculate how much it will cost you to reserve an instance of Snowflake, so you’ll be able to understand whether this product is profitable for you or not before purchasing it.

Data Migration Challenges

Data migration to a Snowflake DB can be a challenge. Snowflake has a unique architecture, different from that of most legacy systems, so transferring data with different structures and formats can cause downtime in business processes. This can be partially avoided if you take care of manual data preparation (at the same time, parallel loading can still cause certain difficulties, especially when dealing with large volumes of data).

Risks of Exceeding Budget

The advantage of high scalability and the opportunity to pay only for what a customer needs has its downsides when it comes to specific bills. Thus, Snowflake software applies no data limits to computing and storage. Companies can easily exceed the use of their services and discover it only during billing. However, to manage costs, they can use built-in Snowflake tools, like Snowsight dashboard and Resource Monitors. Therefore, in the end, this issue can be solved easily.

What Does Snowflake Do: Use Cases

Once we’ve basically answered the question, “What does Snowflake do?” it’s time to address the question, “How exactly can Snowflake be applied?”

Let’s look at a brief overview, explaining the answer to the question, “What is Snowflake used for?”

Arranging Efficient Data Streams

Modern companies typically receive data from multiple sources. Therefore, quick data ingestion for instant use can be challenging. Snowflake relieves the issue with the help of Snowpipe: a continuous data ingestion service that allows for quick and convenient data load from external locations, including Azure Blob, GCP bucket, and S3. 

Implementation of Business Intelligence

All business intelligence operations heavily rely on quality data, making data warehousing a crucial part of the process. Data warehousing is a vital constituent of any business intelligence operation. Companies can build Snowflake data storages expeditiously and use them for ad-hoc analysis by making SQL queries. In addition, they can take an advantage from using built-in options like Snowpark, or integrations with Streamlit or numerous business intelligence tools, including PowerBI, Looker, and Tableau.

Machine Learning Integration Opportunities

Organizations harness machine learning (ML) algorithms to make forecasts on the data. ML models, in turn, require significant volumes of adequate data to ensure accuracy. Moreover, each experiment must be supported with copies of entire data sets. Snowflake cloud platform has a zero-copy cloning feature to conduct this operation seamlessly. The platform also provides all the required integrations to help engineers prepare data and build ML models.

Data Security and Governance

Maintaining data security is crucial for any company. With traditional data warehouses, organizations may find it challenging to prevent data breaches. Snowflake is easy to connect with data governance tools like Informatica and Immuta for maximum data protection and data access under complete control.

Snowflake Architecture

Snowflake architecture represents a fusion of conventional shared disk architecture and shared-nothing database architecture with massively parallel processing (MPP).

In a nutshell, this technology manages to get the best of both worlds. It keeps all the information in a central data repository attributed to a shared disk architecture. At the same time, it applies MPP, which is part of a shared-nothing architecture, to enhance computing power.

Furthermore, a shared-data approach stems from this efficient combination. The background for the Snowflake architecture is metadata management, so customers can enjoy an additional opportunity to share cloud data among users or accounts.

As it was mentioned earlier, Snowflake separates computation and storage. This delivers considerable benefits to organizations with vast storage and low CPU. Snowflake architecture comprises three fundamental layers:

• Cloud services layer: A place that provides complementary features users may need
• Compute layer: A place for data processing
• Database storage layer: A place where data undergoes compression, partitioning, clustering, and other types of optimization

Best Practices for Data Engineering with Snowflake

It’s worth considering the existing experiences to make the maximum benefits out of the Snowflake cloud platform. Here are some key recommendations for Snowflake use according to customer reviews and available options:

Follow the Standard Ingestion Pattern

It’s better to adhere to a multi-stage process of landing the files in cloud storage and loading them to a landing table before transforming the data. You’ll ease orchestration and testing by splitting the whole process into predefined steps.

Preserve the History of Raw Data 

It makes sense to retain the raw data history, which you can store with the VARIANT data type to enable automatic schema evolution. This way, you’ll be empowered to truncate and reprocess data if bugs are detected and provide an excellent raw data source for data scientists.

Use Multiple Data Models

With on-premise data warehouses, storing multiple copies of data can be too expensive. You can use Snowflake cloud computing to store raw data in structured or variant format, using various data models to meet the needs. Each model carries its specific benefits and allows for reloading and reprocessing of data in the event of errors.

Load Data with COPY

Both of these features guarantee the quickest and most efficient way to fulfill data loading. 

Avoid Scanning Files

When ingesting data with the COPY command, it’s better to utilize partitioned staged data files. This is the way to reduce the work of scanning excessive numbers of data files in cloud storage.

Transform Data Step by Step

Massive SQL statements that join and process large numbers of tables do not usually guarantee an efficient working process. Such an approach can lead to over-complex code that operates poorly. Conversely, splitting the transformation pipeline into multiple steps and writing results to intermediate tables would simplify the code, ease the testing of intermediate results, and expedite performance.

Avoid Row-by-row Processing

The Snowflake system performs its primary roles of ingesting, processing, and analyzing billions of rows at incredible speeds using SQL statements, which operate upon the data set at a time. Row-by-row processing may lead to programming loops that update rows one by one. Therefore, such processing can significantly hamper query performance. Instead, you can utilize SQL statements to process all table entries simultaneously.

Simplify and Win

Experienced data engineers value simplicity. Simple solutions are easier to work with, understand, and diagnose problems.

 What will You Attain with Snowflake?

You can enjoy the following opportunities by using Snowflake cloud data:

• Ease of use and complete automation. A convenient and powerful tool, Snowflake relieves companies from all administrating activities. Furthermore, it offers a wealth of extra features providing much more than merely data storage and analytic queries. The tool allows metadata management, zero-copy data sharing, task execution, masking policies, and more. 
• Superior data protection. Snowflake guarantees data security with AES 256 encryption. Even the most sensitive business data will obtain reliable protection as Snowflake is SOC1, SOC2, HIPAA, and PCI DSS compliant.
• Cost efficiency. You can manage your costs easily thanks to the separated data storage and computing resources. Moreover, you’ll have access to real-time information about your spending and the instant opportunity to optimize your costs.
• Flexibility. By using Snowflake DB, you’re free to select or change your preferred cloud provider or infrastructure 

How to Get Started with the Snowflake Cloud

If all the remarkable features and advantages of a Snowflake warehouse have convinced you to implement or migrate to this platform, here are several tips on where to start:

Learn Snowflake Documentation 

Before you start using the Snowflake service, familiarize yourself with the respective documents. Explore the information about getting started, creating an account, and organizing your working processes, such as using REST API to access unstructured data.

Check the Opportunities for Partner Integrations

Snowflake offers an ecosystem of third-party integrations. If you’re already utilizing any software to work with data, you can check which options Snowflake data storage provides. Furthermore, the platform enables connectivity with multiple technologies, including business intelligence tools, machine learning solutions, data science platforms, and more.

Study the Pricing Options

Snowflake has four pricing plans: Standard, Enterprise, Business Critical, and Virtual Private Snowflake. Check the pricing guide and figure out which plan suits your business best.

Join the Snowflake Community

Although the Snowflake community is not so big yet, it may still help you get the answers to your questions or more detailed information on the topics of interest. You can also visit Snowflake’s YouTube channel, which offers valuable content.

Attend Snowflake University

Snowflake has an online university that aims to educate users with all levels of expertise through a variety of courses.

Conclusion

To answer the main question of this article “What does Snowflake do?”—we would like to highlight its following use cases:

• Cloud Data Platform: Snowflake provides a unified platform for all your data needs, from warehousing and lakes to engineering and science.
• Scalability and Performance: Snowflake allows for independent scaling of compute and storage, enabling you to handle massive data volumes with ease.
• Data Sharing and Collaboration: Snowflake enables secure data sharing with partners, fostering collaboration and unlocking new opportunities.
• Zero Management: Snowflake is fully managed, eliminating the need for infrastructure management or software updates.
• Pay-per-use Model: Pay only for the resources you use with Snowflake’s flexible pricing model.

Therefore, whether you’re already applying data management solutions or planning to implement Snowflake as your first data platform, the respective transformation can challenge your organization. 

Now that you know how Snowflake works, you can tackle the task with professional guidance to make your transition a success. NIX has extensive expertise in cloud-based computing solutions. We specialize in bringing innovative technologies to your service. Our experienced team will help you select the optimal tools for your goals, safeguard your data, and manage your entire transformation journey for maximum outcomes.

Entrust your project to our experts, and we’ll identify your unique path to advanced and profitable data operations.