SAP and Snowflake have announced a strategic partnership targeting one of the major bottlenecks in the digital enterprise: connecting, governing, and activating data—SAP and non-SAP—rapidly, with context, and without copies. The alliance integrates Snowflake’s AI Data Cloud as an extension of SAP Business Data Cloud (BDC), enabling zero-copy bidirectional data exchange and promising an “enterprise-ready” experience that combines critical processes and semantically enriched SAP data with Snowflake’s unified platform for analytics, data engineering, and agent-based AI applications.
The approach is compelling: bringing AI to where business data lives without extracting, duplicating, or rehydrating data sets each time a use case is built. “By tightly integrating SAP and Snowflake, we enable companies to connect their critical data with the enriched context already in SAP, supporting seamless and scalable AI application development and data agents within Snowflake,” emphasizes Christian Kleinerman, Senior Vice President of Product at Snowflake. For Irfan Khan, President and Chief Product Officer of SAP Data & Analytics, the key is twofold: openness and freedom of choice within an ecosystem designed for interoperability.
What’s truly new: an “official” bridge, governed, and without copies between SAP BDC and Snowflake
The announcement comes in two complementary parts:
- SAP Snowflake. Integrates Snowflake as a native compute and storage option within the open SAP Business Data Cloud ecosystem. SAP customers can expand capabilities with AI, analytics, Marketplace, and collaboration in Snowflake, working in real-time with SAP data products (semantically enriched) without moving data outside a unified governance framework.
- SAP Business Data Cloud Connect for Snowflake (BDC Connect). Adds zero-copy bidirectional exchange between both worlds. Organizations already using Snowflake can connect to SAP BDC to access SAP data products without duplication, and vice versa. The result: harmonized SAP and non-SAP data, optimized total cost of ownership (TCO), and AI agents/applications fueled by trusted sources with business context.
The collaboration has a timeline: SAP Snowflake will be generally available (GA) in Q1 2026; SAP BDC Connect for Snowflake will arrive in the first half of 2026.
What problems does it solve (and why does it matter for business)
1) AI no longer “chases” the data
Practically, many AI projects stumble over data logistics: extracting from SAP, transforming, moving to another cloud, duplicating for experimentation… and then starting over. The zero-copy approach avoids re-copies and costly synchronizations: agents and pipelines work where the data is, maintaining permissions, policies, and audit trails.
2) Semantic context from day one
SAP data products embed business semantics (entities, relationships, rules) that often get lost in flat exports. By exposing them as-is—and governed—to Snowflake, AI is grounded in organizational knowledge: fewer hallucinations, more explainable and useful responses for finance, supply chain, HR, and customer service.
3) A single fabric of data for SAP and non-SAP
The promise of a unified data fabric materializes: SAP BDC as the orchestrator of semantic value and Snowflake as the platform for analytics, ML, and scale applications. The customer harmonizes their landscape, avoids silos, and ensures data consistency with identity, access control, and auditing.
4) Lower TCO, faster velocity
Each data copy costs: storage, transfer, pipelines, validation, compliance. When no copy, costs decrease and speed increases. That’s why the focus is on zero-copy sharing and elastic compute where data already resides, with SAP support and Snowflake operation.
Use cases ready from today
- Planning and Finance (FP&A): budgets and forecasts that interact with SAP entries, orders, and cost centers, cross-referenced with non-SAP signals (campaigns, weather, third-party inventories). The agent answers what’s happening and why with traceability.
- Supply Chain: near real-time re-planning by combining orders, stock, supplier lead times (SAP), and logistics telemetry (non-SAP). Decisions on replenishments or substitutions supported by auditable explanations.
- Customer Experience: recommendation engines and assistants leveraging SAP history (commercial terms, returns, support) and events in Snowflake (web/app activity, marketing). Less “black boxes,” more context.
- HR and Compliance: complex natural language queries related to roles, training, shifts, and costs, respecting policies and privacy end-to-end.
It’s no coincidence that AstraZeneca highlights benefits in real-time access and analysis; in their sector, every minute of data anticipate counts.
How does “zero-copy” work in practice?
The concept is simple yet powerful: expose datasets between SAP BDC and Snowflake without materializing copies. The compute “visits” the data with inherited permissions, and the catalog (with SAP semantics) ensures that what is queried is what the business recognizes. Behind the scenes, an interoperability layer and governance controls prevent data leaks or unauthorized access. For data teams, repetitive extraction and alignment tasks disappear; for security officers, fewer risk surfaces.
Openness and interoperability: true freedom of choice
This approach combines SAP’s weight in mission-critical processes with Snowflake’s openness (unified engine for AI, analysis, engineering, Marketplace, and collaboration). The message is anti-vendor lock-in: customers can use SAP BDC with SAP Snowflake as a scalable cloud compute and storage option, share data bidirectionally, and build AI where it makes sense. If a company already runs Snowflake, BDC Connect simplifies zero-copy integration without re-architecting their environment.
Security and governance: turning demos into production
All of this relies on trust. The partnership emphasizes:
- Unified governance: identity, permissions, lineage, and audit trails consistent across SAP and non-SAP systems.
- Privacy by design: data stays inside its perimeter; computation and agents approach sources with controls.
- SAP end-to-end support: an essential condition for regulated industries (finance, pharma, public sector) and processes with stringent SLAs.
Questions CIOs and CDOs should ask before implementing
- Catalog and semantics: which SAP data products are ready (and prioritized) for zero-copy consumption? How is the semantics versioned?
- Trust zones: which data domains remain in SAP and which are served in Snowflake for AI/applications?
- Metrics and savings: where does lower TCO (storage, ETL, transfers) occur, and where does value increase (delivery speed, quality, adoption)?
- Governance: how are permissions and audit trails inherited? What compliance dashboards support each case?
Timeline and availability
- SAP Snowflake: GA in Q1 2026.
- SAP BDC Connect for Snowflake: GA in the first half of 2026.
Until then, teams can focus on designing adoption: inventorying SAP data products, prioritizing high-impact AI cases, and testing zero-copy in targeted domains.
Looking ahead: less “handcrafted” integration, more context-rich AI
The SAP–Snowflake collaboration addresses a fundamental demand: reducing invisible work (ETLs, copies, syncs) and increasing meaningful work (business modeling, explanation and decision agents, real experiences). If it delivers as promised, companies will shift from asking “Where’s the data?” to “How can we activate it today with guarantees?” And they will do so with openness, semantics, and governance as pillars of a single, integrated bridge.
Frequently Asked Questions
How do “SAP Snowflake” and “SAP BDC Connect for Snowflake” differ?
“SAP Snowflake” integrates Snowflake as a native compute and storage option within SAP Business Data Cloud, expanding capabilities (AI, analytics, Marketplace, collaboration). SAP BDC Connect enables bidirectional zero-copy exchange between SAP BDC and Snowflake, so both can consume data products without duplication under unified governance.
What is “zero-copy sharing” between SAP BDC and Snowflake?
It’s sharing access to datasets without creating physical copies. The compute and agents access data with inherited permissions, respecting policies and traceability. This reduces costs (storage/ETL) and risks (leakage from duplication), and accelerates AI cases by avoiding synchronization delays.
How does enriched semantic SAP data accelerate AI?
SAP data products embed business context (entities, relationships, rules). Exposed via zero-copy into Snowflake, agents and AI applications start from reliable semantics, reducing errors, improving explainability, and shortening time-to-market in finance, logistics, HR, or sales.
What practical steps should a company take to adopt this?
- Inventory prioritized SAP data products and map key non-SAP domains. 2) Define high-impact AI use cases (and metrics). 3) Configure the zero-copy link between BDC and Snowflake in a controlled environment. 4) Pilot with an agent or application and measure TCO savings and delivery time. 5) Scale with unified governance and compliance dashboards.