mirror of
https://github.com/semantica-agi/semantica.git
synced 2026-09-08 04:00:15 +00:00
155 lines
6.5 KiB
Markdown
155 lines
6.5 KiB
Markdown
# 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.
|