10X Faster Snowflake Data Pipelines with Cost Predictability

"What I really appreciate about CData is how it pushes through table creation and eliminates so much of the manual work I had to do with SSIS and Talend. It's just a better, faster solution. We're incorporating Snowflake more and more, and the stronger the relationship is between Snowflake and CData, the better for us—especially as we scale and serve more clients." — Ken Carter, Senior Director of Data and Analytics at Empower Services

According to Gartner, 50% of new system deployments in the cloud are based on a cohesive cloud data ecosystem rather than on manually integrated point solutions. Snowflake has emerged as a leading ecosystem for cloud data centralization and management, with its ability to unify diverse data sources into a single platform, delivering performant data storage for analytics and AI use cases.

In this post, we explore how data integration with Snowflake is a critical foundation for organizations in achieving business outcomes through analytics and AI, some challenges commonly observed by data leaders in this context, and how innovative data teams are overcoming these challenges.

The challenge: Time-to-value and operational overhead

For organizations using Snowflake as their central data platform, the promise of comprehensive analytics and data-driven decision-making often faces a significant hurdle: the operational burden and time-to-value associated with data ingestion. As data ecosystems become increasingly complex, enterprises are tasked with integrating data from a growing number of sources - spanning cloud, on-premises, and hybrid environments. This process is often manual/code-driven, error-prone, and resource-intensive, leading to delays and operational inefficiencies.

Take a CData customer, a leading enterprise in the biotechnology sector, as an example. The company operates in a dynamic data environment, with data streaming in from diverse systems, including manufacturing applications, sales platforms, and financial tools. Managing these pipelines required extensive manual effort and constant adaptation to changes in data structures—schema drift. As the company’s Head of Data Engineering noted, “In most modern enterprises, all applications are constantly changing, which means data structures and metadata are constantly evolving.” This is particularly crucial as Gartner predicts that "organizations that utilize active metadata to enrich and deliver a dynamic data fabric will reduce time to integrated data delivery by 50% and improve the productivity of data teams by 20%".

Empower Services, a healthcare analytics provider, faced a similar dilemma. With legacy pipelines built on SQL log shipping and SSIS, their workflows were brittle and inefficient, suffering from 12-hour delays and manual table mapping requirements. This architecture was not only unsuitable for modern data-driven demands but also created roadblocks for scaling AI and analytics initiatives.

For both companies, the challenge wasn’t just about moving data into Snowflake—it was about reducing the time-to-value while minimizing operational overhead and enabling their teams to focus on strategic, high-value initiatives. These integration challenges delayed insights, increased operational costs, and overall had a detrimental impact on enterprises’ ability to fully experience Snowflake ROI.

Automating Snowflake ingest with purpose-built toolkits

The CData Snowflake Integration Accelerator addresses these evolving needs through an automated approach that has helped organizations like Empower Services reduce their data pipeline runtime by 91%—from 90 minutes to just 8 minutes. This dramatic improvement comes from our purpose-built integration framework that combines three essential capabilities:

• Our Snowflake Ingest Toolkit modernizes organizations’ approach to integrating organizational data into Snowflake, supporting everything from traditional batch loads to real-time Change Data Capture (CDC) from over 270 enterprise sources. For CData customers, this meant automating 80% or more of their data ingestion pipelines, significantly reducing manual intervention and accelerating time-to-insight.
• The Live Data Access Toolkit enables real-time data access from Snowflake to any application, a capability that proved transformative for healthcare analytics providers like Empower Services. By providing native integration with Microsoft tools and seamless connectivity with Salesforce through Lightning Connect, organizations can maintain real-time data synchronization across their entire application landscape.
• Our Cortex AI Integration Toolkit supports the ingestion of both structured and unstructured data, leveraging Snowflake's native Cortex LLM capabilities.

Why modern enterprises choose CData for Snowflake integration

Native ecosystem compatibility
Our direct integrations with Snowflake modules like Cortex and Apache Iceberg support tight integration between data sources and Snowflake. This native compatibility enables customers to accelerate data ingestion and analytics initiatives.

Proven success with leading enterprises
Our solutions are trusted by industry leaders like Johnson & Johnson, NJM Insurance, and Bausch & Lomb. For instance, a global pharmaceutical manufacturer achieved complete automation of their Snowflake data pipelines, establishing a single source of truth for analytics across their organization.

Breadth and depth of connectivity
With support for complex enterprise systems like DB2, Workday, and SAP Hybris, we address the integration needs that other solutions often overlook. This comprehensive connectivity enabled Empower Services to consolidate their entire data infrastructure, eliminating the need for multiple point solutions.

Cross-ecosystem connectivity
Our platform offers the industry's most extensive purpose-built connectivity across ecosystems, supporting both live connectivity and ETL/ELT workflows. This flexibility allows customers to maintain real-time data synchronization while supporting their complex transformation requirements.

Deployment flexibility and optionality
Unlike other solutions that force cloud-only or on-premises-only approaches, we support hybrid access patterns across cloud, on-premises, and direct cloud platform deployments, without requiring an on-premises agent. This flexibility proved crucial for organizations with strict data sovereignty requirements.

Cost predictability
Our volume-independent pricing model eliminates the uncertainty of consumption-based pricing, providing predictable costs as deployments scale. This approach has helped organizations like Empower Services confidently expand their data integration initiatives without fear of unexpected costs.

Looking ahead

As organizations continue to evolve their data architectures, the need for flexible, comprehensive integration solutions becomes increasingly critical. The CData Snowflake Integration Accelerator provides the foundation for this evolution, enabling organizations to build robust, scalable, and efficient data ecosystems that drive business value.

Ready to transform your Snowflake data architecture? Contact us to learn how CData can accelerate your data integration initiatives.