Certified Partnerships
GOLD PARTNER
S/4HANA implementation, ERP process knowledge and system integration.
OFFICIAL PARTNER
Lakehouse-architecture, datavirtualization and AI/ML use cases.
PARTNER
Azure-based platform integration
and .NET development.
“A well-designed architecture
does not simplify the
data, but preserves its
business meaning while
creating a consistent, scalable
structure.”
0 copies
Real-time SAP–Databricks connection without physical data movement
Unified Data Access
Direct, virtualized access between Datasphere and Databricks
SAP DATASPHERE
Business Context and Semantics
A unified, business-oriented data layer for SAP and non-SAP data that preserves corporate definitions and KPI logic.
DATABRICKS LAKEHOUSE
Scalable Data
and AI Engine
Built on Delta Lake, this open architecture brings together data engineering, data science, and AI-based tasks in a single environment.
ONESPIRE INTEGRATION
Bridge Between
Two Worlds
Architecture design, data virtualization, and performance validation that leverage the strengths of both platforms without causing any business losses.
Data Virtualization & Real-Time SAP Integration
Establishing a JDBC-based connection between SAP Datasphere and Databricks without physical data transfer, while maintaining SAP-side access control.
Lakehouse Architecture
Design
Building a Delta Lake-based Lakehouse or modernizing an existing data platform to create a unified foundation for BI, analytics, and AI.
Data Engineering & ETL/ELT Modernization
Even where the classic pipeline is the better approach: designing scalable, Spark-based data processing workflows and optimizing existing ones.
BI, Analytics, and AI/ML Use Cases
Linking SAP business data with external data sources—such as market, meteorological, or digital data—to unlock new analytical and predictive capabilities.
Performance and Cost Optimization
Fine-tuning the partitioning strategy, parallelization, and memory management to ensure that queries remain scalable even with large volumes of data.
Governance & Access Management
Centralized management of data access and control through the SAP source system, in accordance with the logic of the Databricks Unity Catalog.
CASE STUDY
Real-Time Integration of SAP Datasphere and Databricks
For a major regional energy company, Onespire experts validated a data virtualization architecture that avoided unnecessary physical data movement.
The solution connected business transaction data stored in SAP with meteorological data stored in Databricks through a JDBC-based integration.
The project focused on performance, scalability and the practical integration of SAP business data with external information.
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CLIENT a major regional energy conglomerate |
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METHOD JDBC data virtualisation |
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FOCUS Performance & scalability |
Daily run time (seconds, log scale) and the daily rate of increase in run time
Exclusively from SAP: highly scalable, with the lowest growth rate.
Benchmark on the cloud platform: efficient and highly scalable.
A hybrid solution with SAP-side aggregation: the most efficient hybrid approach.
A hybrid solution with aggregation on the Databricks side: difficult to scale.
Copying all the data to the cloud: the slowest option.
The bar lengths show the measured running time on a logarithmic scale; the exact values are listed next to the bars.
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In-depth knowledge of SAP/ERP processes |
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Hybrid legacy integration |
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Local and EU Compliance |
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Long-term partnership |
| We don’t just move data; we also link it together according to business logic—in manufacturing, logistics, and financial processes alike. | We also have experience in integrating the complex on-premises systems that are still dominant in the region with modern cloud-based solutions. | A team of experts who speak Hungarian and are readily available, with a deep understanding of the specific characteristics of the domestic and European regulatory environments. | We don’t just provide technology: we help ensure genuine, long-lasting business value through methodological support and mentoring. | ||||
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In-depth knowledge of SAP/ERP processes |
|
Hybrid legacy integration |
| We don’t just move data; we also link it together according to business logic—in manufacturing, logistics, and financial processes alike. | We also have experience in integrating the complex on-premises systems that are still dominant in the region with modern cloud-based solutions. | ||
|
Local and EU Compliance |
|
Long-term partnership |
| A team of experts who speak Hungarian and are readily available, with a deep understanding of the specific characteristics of the domestic and European regulatory environments. | We don’t just provide technology: we help ensure genuine, long-lasting business value through methodological support and mentoring. | ||
01
Assessment & Architectural Design
Identify the relevant SAP data domains, business scenarios, and objectives, and then select the optimal integration approach.
02
PoC & Data Virtualization
Rapid, low-risk proof of concept using real data, with JDBC-based virtualization or another approach tailored to the situation.
03
Validation & Scaling
Performance testing, partitioning strategy, and fine-tuning of parallelization to ensure that the solution remains stable even when handling large amounts of data.
04
Operation & Further Development
Ongoing support, governance, and the introduction of new use cases as Databricks-based AI capabilities expand.
Adrián Bohner
Head of the Data Science and Analytics Competency Center