Reimagine your data management with Snowflake

  • Big Data

Every company strives to unlock the true potential of data. Snowflake, a cloud data platform, enables businesses to break down data silos and derive meaningful business insights, and build data-driven applications.

Snowflake data engineering can help you unify and query your data to support a range of use cases. Softweb Solutions’ Snowflake consultants look beyond maximizing your Snowflake ROI.

Snowflake implementation includes:

  • Massive scalability of data volumes
  • Seamless and secure data sharing
  • Handling multiple use cases and users

Our Snowflake services

Modernize your data infrastructure and accelerate decision-making

Snowflake’s features

Ingest diverse data typesSnowflake integrates and optimizes structured and semi-structured data as a common data set, without losing performance or flexibility.
Optimized priceSnowflake charges based on the dataa they store and the compute hours per minute. Users are not chargedfor idlee time.
Easy to useWith a familiar query language and a consumption-based business model, the platform provides instant time to value while reducing hidden costs.
Delivered as a serviceSince Snowflake is delivered as a service, it eliminates the cost, time and resources associated with managing the underlying infrastructure.
PerformanceSnowflake is up to 200 times faster than its competitors. It loads data and queries concurrently with no contention.
Encryption and securityThe platform comes with end-to-end encryption, at rest and in motion. There is no need to manage complex security models or algorithms.

Benefits of Snowflake implementation

Consolidate data into a single source of truth

Increase agility and augment insights

Create new monetization streams

Take advantage of a global multi-cloud strategy

Reduce time spent on infrastructure management

Enable greater data access through improved data governance

Our 5-step Snowflake consulting solutions roadmap


  • Business analysis
  • Current technology stack check
  • Decide on features to build and implement


  • Merge data from multiple sources
  • Data transformation and analytics
  • Performance tuning and security evaluation

Support and maintenance

  • Spot trends to provide solid support
  • Support through data-backed recommendations
  • Seamless support and maintenance for Snowflake services


  • Define the migration scope
  • Determine the migration strategy
  • Establish a team and architectural approach


  • Tune Snowflake query performance
  • Optimize data clustering and micro-partitioning
  • Use Snowflake’s auto-scale policy for warehouse resizing
Why choose us for Snowflake consulting services?

Why choose us for Snowflake consulting services?

  • Experienced Snowflake developers: From requirement analysis to implementation, Softweb Solutions has the expertise to provide flexible, agile and robust Snowflake solutions to organizations.
  • Flawless support: Our skilled Snowflake developers and data analytics specialists in data and cloud can support you on any cloud you choose for your Snowflake deployment.
  • Increase your time to value: Our well-crafted strategies and meticulous planning for Snowflake services ensure timely execution and help you find value faster.
  • Proven methodology: Our proven methodology establishes a solid foundation for efficient transformation of your data and analytics value chain in a risk-free manner.

Snowflake architecture


Credit: Snowflake

Frequently Asked Questions

How will you make a transition from the current on-premises data warehouse to Snowflake on time and within budget?

In nearly every industry, data has become an indispensable resource. Organizations that are very successful usually manage their data efficiently. That’s where the data warehouse plays a key role.

Snowflake data warehouse offers immense benefits over on-premises systems. Snowflake implementation gives companies an edge as it increases agility, security, reliability and flexibility to manage and leverage data like never before.

Before discussing how you will make a transition from the on-premises data warehouse to Snowflake, let’s look at what data types you can migrate to Snowflake and how to prepare your data for Snowflake migration.

Let’s look at what data types you can migrate to Snowflake You can migrate all data types, including structured, semi-structured and even unstructured data.

You can store your structured data at any size in Snowflake, according to your needs. Snowflake supports any valid, single-byte delimiters, including CSV and TSV formats. Snowflake also supports certain semi-structured data types, including JSON, Avro, ORC, XML, Parquet, etc. For unstructured data, you need to use Snowflake’s Snowpark. Snowpark enables the storage, processing and querying of unstructured data, such as medical images or call center recordings.

Here’s a three-step process to migrate data from the on-premises data warehouse to Snowflake. The following steps use a CSV example to illustrate the steps involved in simple data migration.

Select and split your data

Use a file splitter like GSplit or an ETL tool to split the large file into smaller chunks. Doing so allows you to take advantage of Snowflake’s parallel processing capabilities.

Migrate data to a Snowflake staging area

Use the SnowSQL command line client to stage the data. Then, a PUT command with the correct Snowflake syntax will begin staging your local files.

Verify your migration to the cloud

Once the process is complete, you’ll have successfully transferred your local CSV files to Snowflake’s internal stages. Using the command ls, you can list all the files in your directory.

Snowflake cloud services offer businesses many features and improvements over traditional on-premises solutions. Plus, migrating from on-premises to the cloud isn’t as daunting as you may have thought – especially with the right custom software developer.

Why is Snowflake all you need for all your data-related needs, or what are the benefits of Snowflake?

With time, the volume, velocity and variety of data keep increasing. Nowadays, any business needs a single source of truth for its operations backed by data pipelines anywhere, anytime. The traditional on-premises data warehouses struggle to meet business needs. That’s where cloud data warehousing comes in.

With cloud data warehouses, data integration is not merely collecting data from disparate sources. Cloud data warehousing also include data readiness, migration, data management and data warehouse automation. The key is choosing the right data integration platform and tool to maintain and grow an organization’s business.

Snowflake is a cloud data warehouse available as software-as-a-service (SaaS). It has a pay-as-you-go model. Snowflake can be hosted on cloud platforms such as AWS, GCP and Azure. In Snowflake’s architecture, cloud services, storage and computing are separate layers. So, one can run multiple workloads in parallel with no resource contention.

Snowflake data warehouse separates compute from storage. Hence, data loads can continue to run on virtual warehouses without interfering with business users who are retrieving data for reporting purposes. Snowflake, an elastic cloud data warehouse, automatically scales up and down according to your needs. That’s how the platform strikes a balance between performance and cost. supports a multi-cluster meaning it can add resources to manage user and query concurrency needs during peak hours. All these solve the resource contention limitations of a traditional data warehouse.

How much does the Snowflake data warehouse cost?

Snowflake’s elasticity and multi-cluster architecture make it popular. Snowflake’s pricing model is based on two consumption-based metrics: compute usage and data storage.

Compute charges

Snowflake charges compute usage through the number of credits you use. The platform consumes your credit based on queries you run or performs a service like data loading with Snowpipe, data analysis with SQL, etc. Considering compute hours you need per hour need per hour for each of your warehouses and the number of warehouses by the size you require, Snowflake has different rates and editions to offer:

Snowflake calls X-Small, Small, Medium, Large, and X-Large to 4X-Large ‘T-Shirt’ buckets. These T-shirts are virtual data warehouses that provide compute resources that power query execution. The platform provides 10 T-shirt sizes. Nevertheless, 5X and 6X are in preview, currently only available on AWS. With each data warehouse, you will consume credits per second of usage.

Data storage charges

Two factors determine Snowflake’s charges for data storage. First, consider the number of bytes you store per month and how frequently you move data between regions or clouds. Automatic compression of all data stored reduces storage costs and the total compressed file size is used to calculate an account’s storage bill.

Snowflake charges are usage-based

In the United States, for example, Snowflake storage costs start at a flat rate of $23 per compressed TB of data stored. Snowflake Standard Edition has a cost of $0.00056 per second for each credit consumed. Snowflake Enterprise Edition costs $0.0011 per second for each credit consumed.

Adopt the platform’s USP: the pay-as-you-go model

With Snowflake’s consumption-based pricing model, you are billed for usage by the second. With the platform’s auto-stop and auto-resume features, you can stop resources you don’t need.

The virtual warehouses run their queries independently and automatically. This is the biggest benefit benefit of using Snowflake. Users can suspend a specific virtual warehouse manually or automatically if no queries are active, with user-defined rules (for example, ‘suspend after two minutes of inactivity.’). Charges are also suspended for idle compute time once the warehouses have been suspended.

Snowflake’s operations are instantaneous, including suspending, resuming, increasing, and decreasing operations. Hence, customers can pay only for their actual use.

How do you plan the successful implementation of Snowflake for a client?

We consider multiple factors when implementing Snowflake. The following are some points to consider based on that:

From deciding the data types the client needs to migrate to Snowflake, and the compute layers they will require to meet their business needs, to cloud services that provide reporting and analytics – our Snowflake developers help plan an end-to-end Snowflake implementation.

The Snowflake implementation journey is complex and involves many things to consider. For example, data loading is not merely loading data into cloud data centers. Here also, whether the client needs bulk loading, runs complex queries, or requires parallel data loading through multiple threads affects data loading speed and quality.

Similarly, data transformation is not limited to using ETL tools. In addition to ETL tools, run the search queries and consider using Snowflake scripts as well. This helps in solving dynamic queries with cursor variables in SQL. By combining these features with functions like Java UDFs and external functions, one can create high-end data transformation logic in Snowflake.

Further, during data transformation, based on managed services like Snowpipe, Streams, Tasks and the frequency of real-time data like streaming or batch, Snowflake costs vary. Moreover, we help clients’ data teams to test and debug the ingested data by breaking down data pipelines into smaller steps, which write results into transient tables.

Additionally, we help clients in selecting the right data warehouse size depending on the diverse query types and clients’ requirements. Our team ensures data security both in transit and at rest during Snowflake implementation. It is not enough to decide the data journey. It is equally imperative to manage and validate the data that flows into pipelines to gain trustworthy, valuable and actionable insights. Hence, we emphasize maintaining quality pipeline data for our clients as well. This optimizes cost and improves query performance by streamlining data loading.

To help clients maximize Snowflake and optimize their data, we take a detailed look at each consideration.

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About Us

Softweb Solutions Inc. assists businesses in spending less time on managing data infrastructure and more time on unleashing the power of their data. Our cloud and data experts collaborate closely with our Snowflake teams to provide management and consulting services for every use case throughout your application’s or database’s lifecycle. Our proven processes, automation and unrivaled cloud expertise, provide you with the quickest time to value.

Do you want to start your journey to a modern cloud data warehouse?

Automate your data processes to handle your data efficiently

Solve your most complex data challenges with our end-to-end Snowflake implementation services.