# Graph storage backends and feature matrix

Semantica separates graph modeling from physical storage. LPG backends are accessed through `graph_store` adapters; RDF backends are accessed through `triplet_store` adapters.

This page is intentionally conservative: it distinguishes between an adapter existing, a feature being generally available with that model, and a backend needing user-supplied wiring.

## Status labels

- `built-in`: adapter implementation exists in Semantica core.
- `tested`: covered by automated integration fixtures or tests.
- `example-only`: usable example exists, but support is not asserted by integration tests.
- `interface/BYO`: interface or integration point exists; bring your own backend wiring.

## Adapter inventory

| Backend | Model | Adapter | Status | Reference |
| --- | --- | --- | --- | --- |
| Neo4j | LPG | `semantica.graph_store.Neo4jStore` | built-in | `cookbook/introduction/09_Graph_Store.ipynb` |
| FalkorDB | LPG | `semantica.graph_store.FalkorDBStore` | built-in | `docs/reference/graph_store.md` |
| Amazon Neptune | LPG | `semantica.graph_store.AmazonNeptuneStore` | built-in | `cookbook/introduction/21_Amazon_Neptune_Store.ipynb` |
| Apache AGE | LPG | `semantica.graph_store.ApacheAgeStore` | built-in | `docs/graph_stores/apache_age.md` |
| RDF4J | RDF | `semantica.triplet_store.RDF4JStore` | built-in | `cookbook/introduction/20_Triplet_Store.ipynb` |
| Apache Jena | RDF | `semantica.triplet_store.JenaStore` | built-in | `cookbook/introduction/20_Triplet_Store.ipynb` |
| Blazegraph | RDF | `semantica.triplet_store.BlazegraphStore` | built-in | `cookbook/introduction/20_Triplet_Store.ipynb` |
| Anzo | RDF | `semantica.triplet_store.AnzoStore` | built-in | `cookbook/introduction/20_Triplet_Store.ipynb` |
| Oxigraph | RDF | `semantica.triplet_store.OxigraphStore` | built-in | `docs/reference/triplet_store.md` |

## Feature matrix

`Yes` means the capability is expected to work with the adapter and graph model. `Partial` means the capability works with model-specific constraints. `BYO` means the user must supply or validate wiring for the backend.

| Backend | Model | Ingestion | Context graph construction | Reasoning/analytics | Provenance | Known limitations |
| --- | --- | --- | --- | --- | --- | --- |
| Neo4j | LPG | Yes | Yes | Yes | Partial | Provenance and context metadata are stored as node and edge properties; relationship properties and stable node identifiers are required. |
| FalkorDB | LPG | Yes | Yes | Partial | Partial | Redis-based; provenance depends on node/edge properties, and multi-graph isolation depends on the selected graph name. |
| Amazon Neptune | LPG | Yes | Yes | Partial | Partial | Use the property-graph endpoint; AWS auth, VPC, and endpoint configuration can affect local tests. Provenance depends on node/edge properties. |
| Apache AGE | LPG | Yes | Yes | Partial | Partial | Runs through PostgreSQL/AGE; Cypher compatibility and property handling can differ from standalone LPG engines. |
| RDF4J | RDF | Yes | Partial | Partial | Partial | Context separation relies on named graphs; triple-level provenance may require reification or graph-level metadata. |
| Apache Jena | RDF | Yes | Partial | Partial | Partial | Named graphs are needed for context separation; backend configuration and transaction behavior matter. |
| Blazegraph | RDF | Yes | Partial | Partial | Partial | Use quads/named graphs for context; IRI stability and graph naming matter for provenance. |
| Anzo | RDF | Yes | Partial | Partial | Partial | Anzo deployments are environment-specific; validate `dataset_uri`/graphmart naming, named-graph support, and provenance mapping. |
| Oxigraph | RDF | Yes | Partial | Partial | Partial | Embedded, single-process store (in-memory or on-disk); named graphs are supported, but there is no separate server process to scale independently. |

## RDF and LPG differences

- LPG backends store context and provenance as graph elements and properties. If a backend does not support relationship properties, some provenance patterns may be degraded.
- RDF backends rely on IRIs, named graphs, and optional reification. Context graphs and provenance are easiest to preserve when the store supports named graphs/quads.
- Ingestion works across both models, but the physical representation differs: LPG stores nodes/edges directly, while RDF stores subject-predicate-object statements.
- Reasoning and analytics should be validated against the adapter's query capabilities, especially for path traversal, property filters, and named-graph queries.

## Minimal connection examples

Prefer the referenced notebook cells for a working setup. The examples below show the intended adapter entrypoints, not a universal connection DSL.

### Neo4j

```python
import os
from semantica.graph_store import Neo4jStore

store = Neo4jStore(
    uri='bolt://localhost:7687',
    user='neo4j',
    password=os.environ['NEO4J_PASSWORD']
)
```

### FalkorDB

```python
from semantica.graph_store import FalkorDBStore

store = FalkorDBStore(
    host='localhost',
    port=6379,
    graph_name='semantica'
)
```

### Amazon Neptune

```python
from semantica.graph_store import AmazonNeptuneStore

store = AmazonNeptuneStore(
    endpoint='your-neptune-cluster-endpoint',
    port=8182,
    region='us-east-1'
)
```

### Apache AGE

```python
from semantica.graph_store import ApacheAgeStore

store = ApacheAgeStore(
    connection_string='host=localhost dbname=agedb user=postgres password=postgres',
    graph_name='semantica'
)
```

### RDF4J

```python
from semantica.triplet_store import RDF4JStore

store = RDF4JStore(
    endpoint='http://localhost:8080/rdf4j-server',
    repository_id='semantica'
)
```

### Apache Jena

```python
from semantica.triplet_store import JenaStore

store = JenaStore(
    endpoint='http://localhost:3030/ds'
)
```

### Blazegraph

```python
from semantica.triplet_store import BlazegraphStore

store = BlazegraphStore(
    endpoint='http://localhost:9999/blazegraph/sparql'
)
```

### Anzo

```python
from semantica.triplet_store import AnzoStore

store = AnzoStore(
    endpoint='http://anzo-host:8080',
    dataset_uri='http://cambridgesemantics.com/Graphmart/your-graphmart-id'
)
```

### Oxigraph

```python
from semantica.triplet_store import OxigraphStore

# Omit `path` for an in-memory store; pass a directory for on-disk persistence.
store = OxigraphStore(path='./semantica-oxigraph-data')
```

Replace hostnames, ports, repositories, graphs, and credentials with values from your environment. For regulated or self-hosted deployments, keep credentials in environment variables or secret storage rather than source code.