ANNOUNCEMENT

Hexaware Positioned as a Visionary in the 2026 Gartner® Magic Quadrant™ for Custom Software Development Services

Gartner, Magic Quadrant for Custom Software Development Services, By Jaideep Thyagarajan, Ryan McKinney, Nathan Davie, 7 October 2026. Gartner and Magic Quadrant are trademarks of Gartner, Inc. and/or its affiliates. Gartner does not endorse any company, vendor, product or service depicted in its publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner publications consist of the opinions of Gartner’s business and technology insights organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this publication, including any warranties of merchantability or fitness for a particular purpose. This graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from Hexaware.

Whitepaper

Accelerating Teradata ETL Performance: Advanced Partitioning Techniques with AWS Glue

Key Takeaways

– JDBC challenges slow ETL processing and inflate operational costs, this whitepaper explains.
– Advanced AWS Glue partitioning techniques break large datasets into manageable, parallel-processed chunks.
– The approach uses PySpark capabilities to overcome traditional ETL performance bottlenecks.
– AWS Glue can seamlessly handle millions of rows across scalable data workflows.

Accelerate Your ETL Performance with AWS Glue

Are you facing Java Database Connectivity (JDBC) challenges that slow your data processing and inflate operational costs? It’s time for ETL optimization with advanced AWS Glue partition techniques.

The approach we take allows you to efficiently manage large datasets, delivering ETL pipeline optimization and ensuring faster insights. Using PySpark capabilities and effective partitioning strategies, we help overcome traditional bottlenecks and achieve a visible boost in ETL performance.

Why Partitioning Matters

Partitioning is essential for ETL transformation as it breaks down large datasets into manageable chunks, giving way to run parallel processing. This simple yet powerful ETL optimization technique unlocks significant advantages, including improved execution speed and optimized resource utilization.

With AWS Glue, you can seamlessly handle millions of rows, ensuring your data workflows are not only robust but also scalable. Our guide will walk you through how to implement these strategies effectively, helping you to improve ETL performance and streamline your data management.

Ready to get started? Download the whitepaper.

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