Breaking SAP Data Silos with a No-Code Bridge to Snowflake

The traditional path that companies take to integrate their SAP data with other sources in a modern cloud platform like Snowflake is  extract, transform, and load (ETL). This is often a costly, time-consuming slog. It involves brittle, hand-coded pipelines that can take months to build and even longer to maintain. This results in valuable insights being locked away, just out of reach.

But what if organizations could bypass the complexity entirely? What if they could build a bridge between SAP systems and Snowflake in a fraction of the time without writing a single line of code?

This is the promise of the new CData Snowflake Integration Accelerator, a solution designed to radically simplify how organizations move their data into and out of Snowflake.

According to CData, the solution can reduce integration build times by 90%. That statistic alone is compelling for any SAP professional who has stared down the barrel of a complex data warehousing project. It represents a noteworthy shift from long-haul development cycles to rapid, agile data delivery.

From 90 to 8 Minutes

This all sounds great in theory, but what does it look like in practice? Consider the story of Empower Services, a healthcare analytics company. It was bogged down by manual, fragile data workflows that took 90 minutes to run. As Ken Carter, their Senior Director of Data and Analytics, noted, “The process was a constant struggle of manual table mapping.”

By switching to CData’s Snowflake Integration Accelerator, Empower slashed its job runtimes by 91%, from 90 minutes to just eight.

“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,” Carter shared.

This operational win resonates because it frees up skilled data professionals from tedious, low-value tasks to focus on delivering insights.

Under the Hood

At its core, the CData Snowflake Integration Accelerator simplifies and automates data. Instead of the old, manual ways of mapping tables and scripting data movements, it offers a no-code environment for data ingestion and live connectivity. It is built on three pillars:

1. The Snowflake Ingestion Toolkit, which uses Change Data Capture (CDC) to pull data from over 270 sources, including on-premise or cloud-based systems like SAP ECC or SAP S/4HANA and other enterprise platforms, and load it into Snowflake. The no-code CDC means companies can synchronize their Snowflake data with their source systems in near real-time without the heavy lifting.
2. The Live Snowflake Data Access Toolkit that allows organizations’ existing applications to query data directly from Snowflake using standard protocols. For an SAP-heavy organization, this could mean feeding live Snowflake data directly into tools like SAP Analytics Cloud or other BI platforms without staging it first.
3. The Cortex AI Integration Toolkit is designed with an eye toward the future. This toolkit directly prepares and pipelines data for AI and machine learning workloads within Snowflake’s Cortex AI. It ensures that a company’s AI models are working with the freshest, most relevant data from its SAP systems.

For an SAP team, this means less time wrestling with complex data services or custom ABAP extractions and more time enabling the business to make data-driven decisions.

What This Means for SAPinsiders

Hybrid integration is here to stay. The days of pure SAP landscapes are fading. SAPinsider research confirms this, noting that 82% of organizations now need to support SAP-to-non-SAP integration. SAP data is a company’s financial and operational heart, but its true value is unlocked when combined with data from other enterprise systems like Salesforce or Workday. The primary challenge has been the complexity of bridging these worlds. Modern accelerators like CData’s Snowflake Integration Accelerator directly address this reality, making blending SAP and non-SAP data the new standard operating procedure.

Data integration is being democratized. For too long, getting data out of SAP and into an analytics platform has required a specialized skillset and data engineering knowledge that created bottlenecks. By offering a no-code, automated solution, CData’s accelerator empowers a broader range of professionals. Now, business analysts, data scientists, and functional SAP experts can also directly connect, ingest, and access the data they need, turning a highly technical task into a self-service capability.

Cloud-to-on-premise is a critical, unavoidable flow. SAPinsider’s Data, Integration, and SAP BTP benchmark report found that 78% of organizations must support cloud-to-on-premise data flows. Thus, a bidirectional data bridge is paramount, and tools that are purpose-built for this hybrid reality, automating complex tasks like CDC, are a core requirement for any modern data strategy.