Unveiling the Power of Snowpark: Revolutionizing Data Processing


According to the Forbes Survey, over 80% of enterprise business operations leaders say data integration is critical to ongoing operations.

This means that organizations are continuously seeking innovative ways to integrate, process, and analyze their data effectively and efficiently. One of the emerging technologies that has received attention from various organizations is Snowpark. It is a powerful data integration tool developed by Snowflake.

Snowpark is designed to provide a seamless and comprehensive solution for processing and integrating data within the Snowflake platform. This article will delve into the key features, benefits, and real-time examples of Snowpark in the process of data integration.

What is Snowpark?

Snowpark is a data integration framework that empowers data engineers, data scientists, and analysts to perform advanced data processing and integration tasks directly within the Snowflake data warehouse environment. It serves as a bridge between the traditional data warehousing capabilities of Snowflake and the flexibility of modern programming languages like Java and Scala.

Snowpark enables users to write custom code, create complex transformations, and integrate third-party libraries, all while leveraging the power and scalability of Snowflake’s architecture. With its advanced features, Snowpark eliminates the need for complex data transfers, accelerates processing speeds, and provides seamless data integration operations.

“30% of Snowflake's customers utilize Snowpark, resulting in an estimated aggregate of 15 million weekly queries” - Snowflake”

Features that Set Snowpark Apart

Let’s understand Snowpark with a simple example. Imagine Snowpark as a super-smart chef in a kitchen full of different ingredients. You, the chef, want to make a delicious meal (answer or insights) using some ingredients (data), but they come in all sorts of shapes and sizes. Snowpark is like your magical assistant chef who knows how to chop, slice, and mix everything perfectly. So, it prepares the mixes and prepares the items (well-curated and fetched insights) to help you cook a perfect dish (reports). Hence, Snowpark takes different types of data from different data sources and blends them together in Snowpark so you can get valuable information without the hassle.

In addition to this, Snowpark offers a range of exceptional features designed to simplify your data transformation tasks. Let’s explore these features:

In-Memory Processing

in memory processing

Snowpark uses the power of in-memory processing to transform data and perform calculations in the system’s memory. This results in lightning-fast processing speeds, enabling real-time analysis and reducing the latency of data integration.

Polyglot Programming Support

Polyglot Programming Support

With Snowpark, developers can write data transformation code using acquainted programming languages consisting of Java, Scala, and Python. This flexibility allows companies to leverage their present developer skills pool and expedite the adoption of  the generation.

Integration with Snowflake's Data Cloud

Integration with Snowflake's Data Cloud

Snowpark seamlessly integrates with Snowflake’s Data Cloud, making it an integral part of the Snowflake platform. This synergy allows users to easily move between information transformation and analysis levels, all inside an equal environment.

Parallel Processing

Parallel Processing

Snowpark employs parallel processing abilities, distributing statistics changes across clusters for optimized performance. This parallelism is, in particular, valuable for handling huge-scale datasets efficiently.

Native Access to Snowflake's Features

Native Access to Snowflake's Features

Snowpark presents local admission to Snowflake’s capabilities and functionalities, ensuring that users can take advantage of Snowflake’s widespread protection, scalability, and records-sharing capabilities.

Explore How Snowpark Makes a Difference

By seamlessly integrating with Snowflake’s capabilities, Snowpark opens doors to enhanced efficiency, collaboration, and insights, all within a familiar environment. So, let’s explore the key advantages that Snowpark brings to the table, revolutionizing the way organizations harness and leverage their data.

Reduces the Overhead

Snowpark is available with the Snowflake subscription, allowing users to access its advanced features without any additional cost. Thus, it enhances the cost-effectiveness and accessibility of Snowflake with no extra charges.

Did you know that with Snowpark, customers have witnessed a median of 3.5x faster performance and 34% lower cost compared to other solutions? – Snowflake

Enhances Data Agility

Snowpark reduces the time and effort required to process data. You can quickly prototype, iterate, and deploy data pipelines without needing to switch between different tools or platforms.

Reduces Data Movement & Maximizes Unified Data Operations

By enabling code execution within Snowflake, Snowpark strengthens the platform’s position as a unified solution for data storage, processing, and analytics. This minimizes data movement and accelerates insights.

As per Snowflake’s recent report, Snowpark provides a 360-degree view of all business and operational metrics, maximizing data operations.

Enhances Team Collaboration and Skill Utilization

Different team members can contribute using their preferred programming languages, leading to more efficient collaboration and effective utilization of expertise.

Maximizes Team Performance with Unmatched Scalability

Snowpark leverages Snowflake’s elasticity, enabling your data processing code to scale up or down as needed, all while maintaining optimal performance. Thus, your data processing code consistently delivers peak performance.

Did you know that Snowpark has decreased E2E pipeline runtime by 87%? – Snowflake

Creates Streamlined Workflow

By enabling code execution within Snowflake, Snowpark strengthens the platform’s position as a unified solution for data storage, processing, and analytics. This minimizes data movement and accelerates insights.

Snowpark's Impact on Organizations
Across Different Business Categories

A Leading Energy Supplying Company

Challenges: The company utilizes data science to enhance customer service, optimize energy efficiency, and assist financially vulnerable users. However, its in-house ML model development platform didn’t always facilitate the necessary insights. The team had to request to get the relevant data from the data lake team, which could take days and involve complexities in managing data security and governance.
Solution: After switching to Snowflake and Snowpark, the company received unparalleled advantages, such as elastic scalability and language-agnostic processing. With Snowpark’s Python and SQL support, it can now seamlessly manipulate data and deploy end-to-end machine learning, vastly improving the previous complex and cumbersome environment without any dependency on the data lake team. With Snowpark, running data science tasks like feature engineering right where the data resides has brought massive efficiency and ease. 

  • Easier access to data
  • Faster ML development and deployment
  • Greater employee and customer satisfaction

A Leading Data Analytics Service Provider in the Life Sciences Industry

Challenges: The company wanted to develop a data analytics suite to simplify the management of large clinical trial data, allowing organizations to focus on insights. However, while creating the suite, the main challenge was dealing with large, complex, and diverse data coming from various sources. The current architecture of the data processing tool was restricted to limited workload capacity, creating hurdles in utilizing the data properly.
Solution: The company switched to Snowpark. It enabled developers to run Python, Java, or Scala custom functions for efficient pipeline, data app, and ML workflow creation, handling everything from development to execution in a serverless manner for these intelligent applications.

  • Easy to handle large volumes of data
  • Handle data coming from multiple sources
  • Faster data processing

Artificial Intelligence and Machine Learning Company

Challenges: The company utilized multiple data science software platforms for data preparation functions and predictive model scoring, which had limitations in SQL usage. This required data transfer to and from Snowflake, resulting in performance issues.
Solution: Now, with the help of Snowpark, the company can harness Snowflake’s performance and governance advantages by running its in-built pipelines entirely within Snowflake. No-code and low-code users can effortlessly leverage Snowflake’s engine through Java User Defined Functions (UDFs) when constructing their data preparation pipelines. This allows them to repackage data preparation functions and execute them within Snowflake for more efficient processing.

  • Seamlessly handle any number of users, jobs, or data
  • Simplified architecture

Unlock the Potential of Snowpark's
Capabilities with DiLytics Insight Solutions

Snowflake and Snowpark have together established streamlined and secure methods for data processing and integration, delivering substantial advantages to diverse organizations. Similarly, DiLytics also provides a wide range of easy-to-use data analytics solutions under the ‘Insight’ brand to help organizations make informed decisions.

DiLytics Insight Solutions are readymade, end-to-end, plug-and-play data analytics solutions. These solutions contain pre-packaged business metrics, reports, and dashboards, and are equipped with pre-built data objects as well as pre-integrated data pipelines. 

To accelerate the data analytics journey, DiLytics with Snowflake offers pre-built solutions for:

Snowflake’s platform architecturally scales computing separate from storage to deliver a truly elastic, performant, flexible, and affordable solution. DiLytics’ pre-built analytics solution delivers a highly integrated data integration tool, purpose-built for Snowflake, that loads and integrates structured and semi-structured data, and transforms that data for organizations to derive insights rapidly.

What’s the Next Step?

Snowpark opens up a new world of possibilities within the Snowflake ecosystem. For organizations already using Snowflake, integrating Snowpark into your data processing toolkit can lead to enhanced efficiency, improved collaboration, and the ability to tackle more complex data challenges. And to make the most of Snowpark’s benefits, DiLytics has partnered with Snowflake. 

With more than a decade of hands-on experience in the data analytics field, the DiLytics team offers a joint solution with Snowflake to accelerate your data processing and data analytics journey. We provide readymade, end-to-end, plug-and-play data analytics solutions that contain pre-packaged business metrics, attributes, reports, dashboards, and more. With our insightful solutions, we have successfully completed over 100 projects, leaving more than 30 happy clients in the commercial and public sectors. We have the best-in-class team and cutting-edge analytics expertise with industry-leading data analytics tools to tailor to your unique needs and ambitious business goals.

Snowpark ebook

Ready to dive deeper into Snowpark’s potential? Explore our comprehensive ebook for exclusive insights and real-world use cases.