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Epistemic Graph

Epistemic Graph logo

A durable graph database and reasoning engine for connected, evidence-rich data.
Property graph · SQL · RDF/OWL · vectors · time · provenance · multimodal records

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Documentation · Capabilities · Interfaces · Status

Overview

Epistemic Graph is a Rust-native database and compute engine for teams building knowledge systems, evidence-led applications, analytics, and agent memory. It stores and queries connected graph records, relational data, RDF/OWL knowledge, vectors, time-series, events, documents, and media through one engine.

Claims can retain their evidence, provenance, confidence, and time of validity, so applications can inspect why information is present and how it changes. Use Epistemic Graph directly through its clients and query interfaces. It also serves as the durable knowledge layer beneath Arbora and Agent Utilities. Epistemic Graph is the database. Agent execution and connector runtimes live in their respective ecosystem projects.

Key capabilities

Capability What it provides
One multi-model engine Property graph, relational tables, RDF, vectors, time-series, events, blobs, and media
Query across interfaces UQL, SQL, SPARQL, Cypher/Bolt, GraphQL, and typed native clients
Semantic constraints OWL reasoning, SHACL validation, and ShEx shape validation
Evidence-aware knowledge Claims, provenance, confidence, contradiction handling, and bitemporal validity
Durable operation Commit-before-ack persistence, audit, change data capture, tenant isolation, and observability
Distributed deployment Single-node operation and an optional cluster build with replication and coordinated placement

Check the capability matrix and generated method ledger for the current behavior of each operation.

Packages

This repository publishes two PyPI packages and one container image, all at the same version.

Artifact Contents Install
epistemic-graph The Python client, the in-process engine module and the numeric kernel. Carries no executable. pip install epistemic-graph
epistemic-graph-server The native epistemic-graph-server executable (Linux x86_64 and aarch64) and epistemic_graph_server.binary_path(). Source in packaging/epistemic-graph-server. pip install epistemic-graph-server
epistemic-graph[server] The client plus the server package pinned to the same version. pip install "epistemic-graph[server]"
epistemic-graph-server image The server binary on a slim base, one tag for linux/amd64 and linux/arm64, built from the server wheel. docker pull <registry-user>/epistemic-graph-server:<version>

Documentation

  • Start here for a guided engine tour.
  • Interfaces explains UQL, SQL, SPARQL, Cypher, GraphQL, vectors, time-series, and clients.
  • Architecture covers query execution, reasoning, storage, and distribution.
  • Deploy Epistemic Graph covers durable server, TLS, containers, and clusters.
  • Operations covers day-two procedures and recovery.

Architecture

People use browser, terminal, desktop, or messaging clients. Arbora serves clients. Agent Utilities coordinates agents. Epistemic Graph stores knowledge. Connectors synchronize source systems.

Epistemic Graph architecture: authenticated interfaces feed a unified planner, which composes graph, semantic, analytical, temporal, and multimodal engines over one durable store.

People use the Agent Web UI, Agent Terminal UI, Geniusbot, or the messaging services hosted by Arbora. The terminal UI reaches Arbora through its REST API. External applications and agents connect through Arbora using MCP, REST, or A2A. Arbora governs the runtime boundary. Agent Utilities coordinates agents and workflows. Epistemic Graph stores and reasons over their durable knowledge. Source systems enter through Agent Connector SDK, which commits typed source data to the graph.

This repository owns Ecosystem projects own
Durable graph and multimodal state, query planning, reasoning, and engine authorization Arbora owns MCP/REST/A2A entrypoints, runtime policy, and frontend hosting
Generated engine contracts and capability truth Agent Utilities owns agents, workflows, skills, evaluation, and the agent control plane
Source-ingestion admission, schema validation, evidence, and provenance commits Agent Connector SDK owns connector execution and source-system adapters
Database and compute execution Agent Web UI, Agent Terminal UI, and Geniusbot provide user-facing clients

Quick start

Install the release wheel and open an in-process graph. This mode is explicit, ephemeral, and needs no server or TLS configuration.

python -m pip install epistemic-graph
python -m epistemic_graph.cli status  # no server is expected in embedded mode
python - <<'PY'
import msgpack
from epistemic_graph.engine import Engine

engine = Engine(persist_dir=":memory:")
engine.create_graph("demo")
engine.add_node(
    "demo",
    "node:hello",
    msgpack.packb({"kind": "Greeting"}, use_bin_type=True),
)
print(engine.has_node("demo", "node:hello"), engine.node_count("demo"))
PY

Expected output:

Status: NOT RUNNING (no PID file)
True 1

For durable storage, authenticated clients, containers, TLS, or clustering, continue with Deploy Epistemic Graph.

Contributing

Issues and pull requests are welcome. See CONTRIBUTING.md for development setup and review gates. Architecture and implementation guidance for coding agents lives in AGENTS.md.

License

Licensed under the MIT License.

Metadata

Release files for epistemic-graph 2.27.4

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epistemic_graph-2.27.4-cp39-abi3-win_amd64.whl CPython 3.9 abi3 Windows x86-64 Details
epistemic_graph-2.27.4-cp39-abi3-manylinux_2_28_x86_64.whl CPython 3.9 abi3 Linux glibc 2.28+ x86-64 Details
epistemic_graph-2.27.4-cp39-abi3-manylinux_2_28_aarch64.whl CPython 3.9 abi3 Linux glibc 2.28+ ARM64 Details
epistemic_graph-2.27.4-cp39-abi3-macosx_11_0_arm64.whl CPython 3.9 abi3 macOS 11.0+ ARM64 Details

Total release size: 40.6 MB

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