Multi-Source Database Migration Topology
Visualizing real-time schema translation and zero-OOM chunked record streaming from two independent source databases into one unified target data warehouse.
Migraflow AI Engine
AI infers target database schema, aligns column data types, and streams chunked records deterministically without RAM spikes.
Built for Reliable, Deterministic Data Migration
Schema Mapping Engine
Parses target database definitions and source schemas to automatically infer column aliases, primary keys, and data type casts with zero manual script editing.
Constant RAM Streaming
Streams data iteratively in cursor batches. RAM consumption remains constant regardless of total dataset size.
Supported Connectors
Native high-speed drivers for PostgreSQL, MySQL, and MongoDB.
Real-Time Job Telemetry
Monitor active migration throughput, row transfer counts, progress percentages, and error logs live.
Token Rotation & Auth
Secure HTTP-only cookie authentication with automated 401 token refresh queueing.
Simple 4-Step Migration Pipeline
Create Local Docker Agent
Deploy the local Docker agent and configure your database credentials securely. The agent introspects source databases to fetch structural metadata without exposing raw data.
Generate Plan
The AI engine analyzes source database metadata to automatically generate an optimal target schema blueprint, including table mappings, column type conversions, and DDL.
Review Plan
Inspect how the target schema will look in an interactive blueprint. Suggest changes using natural language feedback or manual edits to refine and regenerate the migration plan.
Execute & Monitor
Execute the migration through your local Docker agent with bounded batch streaming. Track live row counts, table progress, and WebSocket telemetry in real time.