SOLUTIONS

Data Infrastructure & Migration Solution

Connect business analysis and data model design through database and API integration, large-scale migration, and operations in one continuous flow.

DBridge loads database and API sources into target databases from a batch rule rather than a hand-built migration program, while IntegREST serves data as a REST API from a SQL declaration and keeps every database query and external REST call on record. We connect both products to the business analysis, data model, and deployment environment of each project.

Core Products

DBridge

Register a load rule instead of building a migration program for each database or API source, and the engine tracks what changed and what runs first.

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IntegREST

Serve data as a REST API by declaring SQL, and keep every database query and external REST call on record.

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The source production database is never written to — it is only read, and writes happen only on the target.

DBridge and IntegREST in Operation

Review full screens and close-ups covering DBridge database and API batch rules and API-to-database mapping, plus IntegREST declared APIs, SQL editing, and audit history.

Full DBridge batch-rule screen for database and API sources, populated with synthetic demo data

DBridge · DB and API source batch rules

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Full IntegREST declared API management screen populated with synthetic demo data — IntegREST · Declared API management

Full DBridge screen mapping synthetic API response fields to target database columns — DBridge · API-to-database field mapping

Full IntegREST operations audit log populated with synthetic users and hashes — IntegREST · Operations audit log

Close-up of a DBridge request contract and JSON body editor for a synthetic external API — DBridge · Declared API request contract

Close-up of the IntegREST SQL editor with a synthetic customer table and read-only SELECT statement — IntegREST · Read-only SQL editing

Close-up of a DBridge API test call with masked keys and synthetic request values — DBridge · API test call

Close-up of an IntegREST API test with masked authentication data and synthetic request parameters — IntegREST · Request parameter test

Accounts, internal addresses, business identifiers, and data were replaced with synthetic demo values or masked.

Architecture

ArchitectureExternal databases and REST APIs → business analysis and data model design → DBridge and IntegREST product cores → data/API layers and operations. Specific products and operating environments are selected per SI project.

SUB-SOLUTION 01

Domain Analysis & Data Modeling

We map business requirements through stakeholder interviews, interface mapping, and data-flow tracing, then formalize them as logical and physical data models. We design consistency strategies for keys, indexes, relationships, and history retention to suit each operating environment. Data modeling for enterprise workflows is where our company began and remains one of our longest-developed capabilities.

Stakeholder Interviews & Interface Mapping — tracing business requirements and system touchpoints
Logical Data Modeling — defining entities, relationships, and history requirements
Physical Data Modeling — Consistency, indexing, and partitioning strategies
Data dictionaries, specifications, and migration mapping documentation

SUB-SOLUTION 02

Cross-DBMS Bulk Data Migration

DBridge selects either a database or an API as the source and loads into a target database. It manages DB-to-DB and API-to-DB jobs through the same batch rules, then processes large migrations in parallel using multiple processes and logical partitioning. Idempotent execution and failed-row tracking help operators identify what needs to be retried.

Unified DB and API sources — manage DB-to-DB and API-to-DB jobs through the same batch metadata
Major DBMS adapters — integrates Oracle, PostgreSQL, MySQL, and other project data stores
Parallel migration — RANGE, MOD, ROWID, and HASH partitioning across multiple processes
Operational controls — dual locking, idempotent execution, and failed-row tracking

SUB-SOLUTION 03

Multi-index Synchronized Ingestion & Search Integration

In addition to structured RDBs (DW), we load data into FTS search engines, Graph DBs, and Vector DBs using the same ETL flow. With optional Korean morphological analysis and AI embeddings, we run unstructured text through the same pipeline as well. We integrate keyword, semantic, and relationship search over the same dataset.

Synchronous loading of 4 indexes — RDB, FTS, GDB, Vector DB
Unstructured text processing — Korean morphological analyzer & AI embedding (optional)
Integrates keyword, semantic, and relationship search on identical data
Index distribution strategy is designed separately for each project's data model

SUB-SOLUTION 04

Product Operations & Integrated Traceability

DBridge operations manage batch rules, execution history, and progress. IntegREST operations track declared APIs, call evidence, reconciliation, and audit history. Permissions and alerts integrate with the deployment environment's requirements.

DBridge — batch rules, dependencies, execution history, and progress
IntegREST — declared APIs, public-endpoint tests, and request replay
IN/OUT evidence, daily reconciliation, and a SHA-256 audit chain
Permissions, alerts, and operational statistics integrate with deployment requirements

Use Cases

2025Korean National Police Agency

『Integrated Platform for Protecting Vulnerable Groups (Phase 1)』 Project

Used DBridge to migrate data from four existing systems.
2024Korean National Police Agency

『Next-Generation Forensic Science Platform』 Project

Used DBridge for database synchronization.

The operating environment — data stores, server specs, OS — is sized per SI project according to data scale and requirements. Specific product selection and operating environment are also decided per project.

Considering Cubiware for your organization?

We will guide you through setup and rollout tailored to your requirements and operating environment. Reach out for a demo or a proposal.