Bridging On-Premises and Cloud a Framework for HANA Smart Data Integration in Multi-Stream Data Lake Architectures
DOI:
https://doi.org/10.15662/IJEETR.2021.0302007Keywords:
SAP HANA, Smart Data Integration, Multi-Stream Data Lake, Hybrid Cloud, On-Premises Integration, Data Architecture, Real-Time Data ProcessingAbstract
Enterprises running SAP HANA on premises face a persistent architectural question as they build cloud-based analytics platforms: how to combine core transactional and master data held in HANA with the broader, multi-source data lake environments increasingly hosted in public cloud infrastructure. SAP HANA Smart Data Integration (SDI) provides a native mechanism for federating, replicating, and transforming data across this boundary, but its effective use in a multi-stream data lake context requires a deliberate architectural framework rather than an ad hoc set of point connections
This article presents such a framework. It defines the core SDI architecture, describes a multi-stream data lake model spanning batch, change data capture, and near real-time streams, and proposes a layered reference architecture for bridging on-premises HANA systems with cloud data lake zones. It covers adapter strategy, data flow design patterns, flowgraph transformation practices, performance and sizing guidance, governance and lineage considerations, security architecture, monitoring, implementation methodology, cost considerations, and common risk factors.
The framework is illustrated with simple reference tables covering adapter types, data flow pattern comparisons, sizing benchmarks, and illustrative cost ranges. It concludes with best practices and an outlook on how hybrid on-premises to cloud data integration patterns were continuing to mature at the time of writing in early 2021.
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