
INFOSTRUX IS A CERTIFIED SNOWPARK ACCELERATED PARTNER

Let us bring you to the top of the data mountain.
Apache Spark is a significant force multiplier in the data landscape. Its complexity, however, needs a high operational overhead which leads to cost, challenging performance optimization, and inconsistent governance and security policies.
To address those limitations while further enhancing the overall capabilities of the execution model enabled by Spark, Snowflake has introduced Snowpark, which provides Spark-like DataFrame functionality within a fully managed, secure, and scalable environment.
Infostrux brings its prescriptive approach to help you move your Spark workloads to Snowpark swiftly and reliably.
Key outcomes

30 - 50% platform cost savings through reduction in data movement and more efficient compute within Snowflake

2 - 5x performance improvements by leveraging Snowflake scalability features

30 - 40% decrease in engineering effort

1.5 - 2x faster project delivery through simpler, more reliable, and easier to maintain computing environment

70 - 80% SLA shortfalls, incidents, and failures reduction by relying on Snowpark

Enhanced security, traceability, and audit capacity of data through Snowflake’s native data governance controls
Use Cases
Typical challenges addressed by migrating to Snowpark include:
- High cost and complexity of maintaining multiple environments
- Inconsistent performance and reliability
- Lack of cluster scalability
- Rigid environment disallowing experimentation
Proof of Concept
Goals
- Cost savings validation
- Validation of performance and scalability improvements
Activities
- Discovery and planning
- Solution architecture
- Code conversion readiness evaluation
- Automated and manual code conversion
- Cost savings, performance, and scalability evaluation
Delivered at no cost by Snowflake Sales Engineering and Infostrux
Full Scope Migration
Activities
- Full-scope migration planning
- Solution architecture
- Snowflake environment preparation and CI/CD setup
- Automated and manual code conversion and redesign
- Re-engineering of ingest and egest data flows
- Historical data migration
- Migration validation and testing
- Snowflake environment optimization