🛣️ Roadmap

# 🛣️ Roadmap

Below is **a high-level road map view for GraphAr to provide a sense of direction of where the project is going**. This can change at any point and does not reflect many features and improvements that will also be included as part of the journey along this road map.

## Format
- Support multi-labels for vertex and edge
- Standardizing the format v1 specification

## Integrate with other graph systems

[related disscusion here](https://github.com/apache/incubator-graphar/discussions/918)

- [x] Neo4j, refer to [this blog](https://graphscope.io/blog/tech/2023/09/14/Import-and-Export-Graph-Data-of-Neo4j-with-GraphAr) or [our document](https://graphar.apache.org/docs/libraries/spark/examples#importexport-graphs-of-neo4j)
- [x] [GraphScope](https://github.com/alibaba/graphscope)
- [ ] NeuG, refer to [this blog](https://graphscope.io/blog/tech/2026/04/12/neug-one-engine-two-modes)
- [ ] support loading GraphAr to HugeGraph through its [loader](https://github.com/apache/hugegraph-toolchain/tree/master/hugegraph-loader) (first), and export to GraphAr (later). related info:
- [issue at HugeGraph toolchain](https://github.com/apache/hugegraph-toolchain/issues/574)
- [privous disscusion & exploration](https://github.com/apache/incubator-graphar/discussions/343)
- consider: loading with
- GraphAr Java SDK(rely on #756) & [HugeGraph loader](https://github.com/apache/hugegraph-toolchain/tree/master/hugegraph-loader)
- GraphAr Java SDK(rely on #756) & [HugeGraph client](https://github.com/apache/hugegraph-toolchain/tree/master/hugegraph-client)
- [Spark SDK](https://github.com/apache/incubator-graphar/issues/357)
- (not sure) support loading GraphAr to [cuGraph](https://github.com/rapidsai/cugraph) to make GPU-accelerated graph processing more convenient.

## Libraries

### C++ Library
- Format compatibility to v1
- Make full use of feature of columnar format parquet/ORC to improve
read/write performance
- A simple out-of-core compute engine base on graphar

### Java / Scala with Spark Library
- Format compatibility to v1
- Modularize the library: split to info/reader/writer...
- Integrate with ldbc_snb_datagen_spark[1]

### Python with PySpark
- A new PySpark API that work with both Spark Classic and Spark Connect

### Rust Library
Tobe recorded.

#### Others
- ETL CLI for graphar data [2]
- More language binding
- Construct a DataHub with GraphAr format

[1] https://github.com/apache/incubator-graphar/issues/463
[2] https://github.com/ldbc/ldbc_snb_datagen_spark