ORLANDO, Florida., September 2, 2025 – Snowflake has announced the public preview of Snowpark Connect for Apache Spark™, a groundbreaking advancement that allows organizations to execute Spark workloads directly within Snowflake warehouses, without the overhead of maintaining Spark clusters. With the arrival of Snowpark Connect for Apache Spark, enterprises can now modernize how they process data at scale while ensuring performance and governance remain top priorities.
For years, many enterprises relied on the Snowflake Spark Connector to process data, which often introduced challenges like data movement, higher costs, latency, and governance risks. Snowpark Connect for Apache Spark in Public Preview eliminates these hurdles by enabling Spark code execution natively in Snowflake, preserving data integrity, accelerating performance, and simplifying governance.
Why This Matters: A New Era of Simplicity
Traditionally, Spark environments required constant care, managing dependencies, ensuring version compatibility, and juggling costly infrastructure upgrades. With Snowpark Connect Spark integration, all of this complexity disappears.
Built on Spark Connect, a client-server architecture introduced in Apache Spark 3.4, the solution decouples user code from the Spark cluster. Snowflake extends this foundation by allowing Spark SQL, DataFrame operations, and user-defined functions (UDFs) to run directly within its elastic virtual warehouses.
The result? Seamless integration where businesses keep their Spark code, while Snowflake handles scaling, tuning, and runtime management behind the scenes. For a real-world example of Snowflake’s impact, explore Prolifics’ Snowflake success story.
Performance and Cost Benefits
Snowflake reports impressive results from early adopters. Customers using Snowpark Client see:
- 5.6x faster performance compared to managed Spark solutions
- 41% cost savings through reduced infrastructure and operational overhead
By cutting out the need for data movement and cluster maintenance, enterprises not only save money but also gain the agility needed to respond in real time to business demands.
To further enhance usability, the Snowpark Connect Public Preview ensures that modern Spark APIs, DataFrames, Spark SQL, and UDFs remain supported, so teams don’t need to rewrite code to benefit from these enhancements.
Governance and Open Data Integration
In today’s compliance-heavy environment, centralized governance is critical. Snowpark Connect for Apache Spark strengthens security by keeping all processing within Snowflake’s unified compliance framework.
The solution also integrates seamlessly with Apache Iceberg, supporting both internally and externally managed tables as well as catalog-linked databases. This further aligns with Snowflake’s strategy of advancing into the open data ecosystem, empowering organizations to leverage data more flexibly and efficiently. With Snowpark Connect Spark integration, companies can maximize both compliance and performance in their open data workflows.
What’s Next: Current Limitations
Snowpark Connect for Apache Spark in public preview currently supports Spark 3.5.x and is limited to Python environments, with Java and Scala support in development. Some Spark capabilities, including RDDs, Spark MLlib, and streaming APIs, are not yet available. However, the roadmap promises rapid evolution as Snowflake continues to expand compatibility and functionality.
Supported clients include Snowflake Notebooks, Jupyter, VSCode, Airflow, Snowflake stored procedures, and Snowpark Submit, giving developers multiple options to integrate with existing workflows.
The Prolifics Advantage: Unlock Real Business Value
While Snowpark Connect Public Preview is a technological leap forward, unlocking its full potential requires the right expertise. That’s where Prolifics comes in.
At Prolifics, we help enterprises:
- Migrate and modernize Spark workloads to run seamlessly in Snowflake
- Optimize data pipelines for performance, cost efficiency, and governance
- Leverage open data architectures like Apache Iceberg for future-proof flexibility
- Accelerate analytics and AI initiatives with real-time, compliant, cloud-native data solutions
Our experts bridge the gap between technology innovation and business outcomes, ensuring your organization doesn’t just adopt new tools but transforms how data drives growth.
Ready to Reimagine Spark in Snowflake?
Snowpark Connect for Apache Spark is more than an upgrade, it’s a reinvention of how enterprises handle Spark workloads. By eliminating clusters, simplifying governance, and cutting costs, it sets the stage for next-generation analytics and AI innovation.
Talk to Prolifics Experts today to explore how Snowpark Connect for Apache Spark in Public Preview can transform your data strategy and position your business for the future.
Media Contact: Chithra Sivaramakrishnan | +1 (646) 362-3877 | chithra.sivaramakrishnan@prolifics.com
