TY  - JOUR
T1  - Dual Storage Engines toward Multi-Model Analytic Workloads
AU  - Koo, Kyoseung 
AU  - Choi, Yoojin 
AU  - Kim, Bogyeong 
AU  - Moon, Bongki 
JO  - Journal of KIISE, JOK
PY  - 2026
DA  - 2026/1/14
DO  - 10.5626/JOK.2026.53.2.158
KW  - multi-model
KW  - analytic workloads
KW  - storage engine
KW  - join algorithm
KW  - database system
AB  - Modern data analytic workloads increasingly require handling multiple data models
simultaneously. Two primary approaches meet this need: polyglot persistence and multi-model
database systems. However, they are limited by high communication costs due to the physical
disaggregation of the system or inefficient query processing stemming from reliance on a single
engine. To address these limitations, we present DSE, a multi-model analytic system with integrated
storage engines optimized for each model. DSE treats all data models as first-class entities, composing
query plans that incorporate operations across models. To effectively combine data from different
models, the system introduces a specialized inter-model join algorithm called multi-stage hash join.
Our evaluation demonstrates that DSE outperforms existing approaches on multi-model analytics,
confirming the effectiveness of our proposed techniques.