SnowFlake: The Best Data Warehousing and Prescriptive Analytics Solution

10 minutes


Data Warehouse as a Service, or DWaaS, has gained much popularity in the past decade. It is a service primarily provided by Snowflake Inc, and it has been since 2012. However, today, some big names provide the same services, including Microsoft, IBM, Google, and Oracle. Selecting the right one according to your business’ data management requirements is essential.

The right platform maintains agile data warehousing, prescriptive analytics, and storage principles to help your business grow. So, here we will discuss whether Snowflake is the best DWaaS for you.

What Is Snowflake Computing?

Snowflake is a data solution to scale and fulfill enterprise data warehousing needs while minimizing the enterprise’s maintenance and workload connected to data storage. It is a cloud-based service available in Google Cloud, Microsoft Azure, and AWS that does not require hardware management.

Based service available in Google Cloud

These data warehousing solutions need no installation, software management, or configuration with your business solution. Today you may find several cloud data warehouse solutions for data storage and processing. However, Snowflake comes with several factors that distinguish it from others.

How Does Snowflake Benefit a Business?

Businesses have some distinct and overlapping requirements from the data warehouse provider. Snowflake brings several benefits for all those requirements.

  • No Need for Maintenance

Using Snowflake to manage and analyze data will never require any maintenance. While other database administrators rely solely on routine maintenance for their data warehouse solutions to ensure reliability and performance, that’s not needed with Snowflake.

  • Security and Encryption with Cloud services

Snowflake lets users manage their infrastructure by optimizing their data using the ANSI SQL cloud services. It handles the encryption of the data to maintain certifications like HIPAA and PCI DSS, so your infrastructure integrity and data security will retain meaning.

ANSI SQL cloud services

It uses query parsing, authentication, metadata management, query optimization, and access control features to maintain those certifications robustly.

  • Database Storage Services

Your enterprise may upload semi-structured or structured data here. Snowflake will process that data and automatically manage its analysis, storage, organization, metadata, compression, statistics, structure, and file size.

  • Easier Automation

With Snowflake, there is no need for manual data management or maintenance, as it simplifies automation. Snowflake allows automating the:

  • Availability
  • Security
  • Management
  • Governance
  • Resiliency

of your data. Thus, your enterprise can enjoy an optimized performance with greater capacity, less downtime, and cheaper overall costs. It improves the overall system efficiency for every business with high reliability achieved through automation.

  • Efficient Query Processing

The compute layer is made from virtual cloud warehouses where you can analyze data through query requests. Every virtual warehouse is an independent cluster, and one does not affect the performance or resources of the other.

Efficient Query Processing

So, workload concurrency will never be a problem with Snowflake. Efficient query processing is one of the best benefits of the Snowflake cloud migration strategy.

  • Scaling

Snowflake uses SQL, which allows enterprises to scale their computing units easily and efficiently without creating redundancy. It also helps separate storage from computing hardware for an instant scaling experience with no downtime.

With Snowflake, you can use a code line to resize computing units while scripting the data transformation. All this can be done without waiting for the load balancing of current data clusters or stopping current workloads.

The single elastic performance engine delivers high performance and allows instant scalability. The multi-cluster resource isolation gives businesses the performance they need to manage concurrent workloads. With its analytics, feature engineering, interactive application access, and complex data pipelines, users with all skill sets and businesses of all scales can leverage their data.

  • Personal Assignments

With Snowflake, your on-site team can focus more on core business goals, and the database team can get insights using prescriptive analytics on end-user data. Centralized data allows your team to make actionable informed decisions.

  • Disk Requirements

Snowflake eliminates issues like the lack of data on disk drives or the lack of computing power required for data transfer and big data analytics. The cloud data warehouse from Snowflake ensures that all database-related disk requirements can be solved with optimization, architecture, and database modeling performed by your on-site team.

  • Modernization Over Data Cloud

Snowflake centralizes vast amounts of data over data cloud solutions. So, concurrent users and applications at your enterprise can seamlessly use that data.

  • Better AI and ML Performance

Snowflake accelerates Machine Learning and Artificial Intelligence features with its analytics engine. The high-performance data, in combination with higher computing power, brings infinite possibilities to automate workflows instantly.

How to Scale Your Business with Snowflake

With Snowflake, you can start scaling your business by distinguishing between computing and storage options. Through this process, your business gets on-demand scaling for each of these operations, and Snowflake provides transparent information about your requirements.

It supports spinning new data clusters that can instantly implement systems that, if you implement with on-premises hardware, would take up to months of setting up and configuration.

Snowflake automatically scales resources without harming performance, uptime, or data accuracy. Traditionally, scaling can take weeks because data is spread across several sources. Snowflake centralizes data for instant scaling. Thus, it provides newer growth opportunities for your business.

Critical Business Problems You Can Solve with Snowflake Data Warehousing

Using Snowflake data warehouses and data services solves several critical business problems. So, here are the top reasons to consider Snowflake.

  • Performance Bottlenecks Can Be Solved with Centralization

When you store data with snowflake data warehouses, it is stored in one centralized location. A higher number of raw data sources can create a spaghetti architecture problem that results in bottlenecks for your performance. With data centralization, this is solved effectively and instantly. Managing data lakes for your engineers also gets easier.

Snowflake can consolidate data pipelines with DBT and Fivetran. Thus, Snowflake supports effective data science utilization to make nearly real-time decisions. These sensitive data-driven decisions with machine learning can result in better bottom-line revenue.

  • Improved Performance as You Scale with a Data Warehouse

Your business application or dashboard running slower can be a data engineering issue that needs an instant solution; otherwise, your business may lose revenue. A lack of scalability from data warehouses can make your business face unnecessary growth bottlenecks. With Snowflake, your application’s processing speed increases by up to three times.

Because of effective scaling and data management, your business intelligence can derive new insights quickly. Additionally, this scaling results in quicker iterations when developing and testing soft solutions.

  • Cost Saving by Paying for Only What You Use

Cost is a primary consideration for many businesses when selecting data warehouses. Snowflake brings efficient pricing solutions by separating computing and storage hardware. You can pay for these separately and only for the resources used. So, you will only be paying for the queries executed on the data platform, which results in lower costs.

Snowflake also allows you to switch to larger data warehouses whenever needed for a specific query. Scaling back to the original warehouse unit is seamless when you are done with that. Thus, the cost savings are massive when you compare Snowflake to traditional data warehouse solutions and on-premises hardware.

  • Informed Decision Making Through Data Analysis and Meaningful Insights

The Snowflake data warehouse leaves more time and money to be spent on different types of analysis. Through better analytics from the data lake, your data engineers can improve the front end of your application according to market trends. Senior management can focus on informed decision-making with meaningful insights from your business data.

The 5 Best Data Warehouse as a Service Alternatives to Snowflake

The following are the leading DWaaS alternatives to Snowflake.

1. Amazon Redshift

Amazon Redshift integrates with the AWS environment and your data lake, allowing developers to query data seamlessly in both structured and semi-structured forms. It provides enterprise-grade performance with the AWS reliable data infrastructure for the best user experience.

Amazon Redshift

AWS Glue helps extract and transform data to load in your data warehouse if it is unavailable in the S3 data lake. It supports 1 billion GB of data, meaning unlimited storage. However, it is a more technical platform than Snowflake, meaning a management team will be necessary.

2. Google BigQuery

This part of the Google Cloud environment brings a serverless cloud data warehouse that is highly scalable and provides low-cost services. It instantly provides reliable data analytics.

Google BigQuery

BigQuery differentiates itself from its competitors based on its integration capabilities with machine learning tools. Its plug-and-play solutions provide up to 10GB of free cloud-based storage and a simple user experience.

3. IBM Db2 Data Warehouse

This relational database on the IBM cloud provides top-notch data management and quality analytics solutions. It offers a significant improvement in performance over its competitors with integration with the in-memory columnar IBM database engine.

IBM Db2 Data Warehouse

A special version of the Db2 warehouse is also available if your business requires an on-premises solution.

4. Microsoft Azure

Microsoft Azure

Azure Synapse from Microsoft is a solution that combines big data analytics and cloud data warehousing. Querying in this data platform is easier and more efficient as you can use serverless and provisioned resources. It also brings machine learning capabilities within your data framework with industry-leading privacy and security.

It is easier to use because of Microsoft’s integration with the SQL server. Azure enhances security by dynamic data masking, where sensitive data is masked from users without access. It also provides end-to-end data monitoring and some business tools from the Microsoft Suite.

5. Yellowbrick Data

Yellowbrick Data provides a data warehouse solution for the hybrid cloud, making it simpler for every business. It focuses on optimized analytics. Businesses using this platform can run any ad hoc query or concurrent queries to generate business reports.

Yellowbrick Data

Yellowbrick Data ensures the best performance through its 24/7 predictive monitoring for the availability and health of the warehouse infrastructure.

Top Use Cases of Snowflake

Any enterprise can benefit from several use cases of moving to Snowflake. Below are some specific use cases that may help your business.

  • Data Sharing. If your business needs to share data with third-party accounts, then Snowflake can offer better security for your data-sharing requirements. You will never need to leave a copy of the data you share on your centralized servers. It estimates data silos and ETL with cross-region and cross-cloud connections. Whenever someone needs data, they get a copy from the cloud while the actual data remains unchanged. A single shared data source enables better remote collaboration with a single source of truth.
  • Third-Party Integrations. Snowflake helps extend business workflows with third-party app integrations. You can use any iPaaS to automate those third-party workflows to connect well with your customers.
  • Analytical Workloads and BI Reporting. Snowflake provides premium performance with its business intelligence analytics tools. The analytical workloads and BI reporting run instantly on Snowflake’s data warehouses.
  • XML and JSON Support. Snowflake has better support for semi-structured data sources like JSON and XML.

Thus, Snowflake provides better performance, security, and data organization than your on-premises hardware, and it combines this with an amazing customer experience.

Final Remarks

Snowflake is the best DWaaS solution for most businesses considering the features, efficiency, and speed it offers. Snowflake Inc is still rapidly growing, with a value of over $13 billion. Considering the competitor options in the market, the performance of Snowflake helps it stay competitive against tech industry giants like Google and Microsoft.

So, if you want to take your business growth to the next level, Snowflake might be the best solution for all your cloud data warehousing needs. Feel free to contact us to learn more about these services.