Overview

NeuG provides a set of tools for moving data in and out of your graph database.

Architecture

The data ingestion pipeline in NeuG is built around a layered design:

External Files (CSV, JSON, Parquet, ...)
        │
        ▼
   ┌───────────┐    Schema inference, relational operations
   │ LOAD FROM │    (projection, filtering, type casting, aggregation, ...)
   └────┬──────┘
        │  Unified internal format
        ▼
   ┌───────────┐    Persist into graph storage
   │ COPY FROM │    (requires predefined schema)
   └───────────┘

LOAD FROM is the foundation of data ingestion. It reads external files, automatically infers the schema, and produces a temporary result set. You can apply relational operations — such as column projection, type casting, filtering, and aggregation — directly on the loaded data.

COPY FROM builds on top of LOAD FROM. It takes the result of a LOAD FROM operation and persists it into graph storage. Because COPY FROM uses LOAD FROM internally, any file format supported by LOAD FROM is automatically available for COPY FROM as well.

COPY TO works in the opposite direction — it exports query results to external file formats.

Supported Formats

Note: As new format extensions are developed, both LOAD FROM and COPY FROM gain support automatically. See the Extensions page for details.

What’s Next

• LOAD FROM — Read external files into temporary tables with relational operations
• COPY FROM — Persist external data into graph storage
• COPY TO — Export query results to external files