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- Product: BogDB
The embeddable graph database
for .NET and the AI era.
A native .NET property-graph database with Cypher, a full Graph Data Science suite, window functions, native MCP servers, and a planner-integrated extension surface. Apache 2.0 — built for the AI era when your agents and your application share the same graph.
For engineering leaders, platform teams, and AI/data architects building durable, queryable systems on .NET.
Apache 2.0. Clone it and open a graph in your next checkout.
using BogDb.Core.Main;
using var db = BogDatabase.CreateInMemory();
using var conn = new BogConnection(db);
conn.Query("CREATE NODE TABLE Person (id INT64, name STRING, PRIMARY KEY(id))");
conn.Query("CREATE REL TABLE KNOWS (FROM Person TO Person)");
conn.BeginWriteTransaction();
conn.Query("CREATE (:Person {id:1, name:'Alice'})-[:KNOWS]->(:Person {id:2, name:'Bob'})");
conn.Commit();
var r = conn.Query("MATCH (a)-[:KNOWS]->(b) RETURN a.name, b.name");Why BogDB exists
The graph-database landscape circa 2026 has a hole in it. Neo4j is JVM-first and copyleft. DuckDB does columns, not graphs. Upstream Kùzu — the embeddable, permissively-licensed graph database many of us were standardizing on — was acquired into a private roadmap, with the public project archived after its last 0.11.x release.
BogDB is the answer for everybody else: an actively-maintained, embeddable, .NET-native graph database under a permissive Apache 2.0 license. The current engine ships a 226-function scalar catalog — roughly twice the upstream surface — alongside full ROWS / RANGE / GROUPS frame-clause window functions, an expanded Graph Data Science algorithm suite, native Model Context Protocol servers, and a planner-integrated extension surface that lets you plug custom indexes into query optimization without modifying or forking the engine. The core started as a test-by-test parity port of Kùzu's C++ engine; what ships today extends well beyond that foundation.
BogDB is built by Beyond Ordinary Software Solutions and lives at github.com/BeyondOrdinary/BogDB.
What's inside
Three intersecting capabilities, all in one embeddable .NET assembly.
Cypher at C++ parity
Property-graph data model, ANTLR4 Cypher parser, planner with all twelve optimizer rules at upstream parity, 226 scalar functions, 13 window functions with full ROWS / RANGE / GROUPS frame clauses, and ten Graph Data Science algorithms (PageRank, WCC, SSSP, SSSP Path Reconstruction, K-Hop, VLP, Louvain, SCC, K-Core, Span Forest). Disk-backed columnar storage, MVCC, WAL with page-level recovery.
MCP in the box
Native Model Context Protocol servers ship with the engine. Vector and LLM extensions are built in. Natural-language Cypher generation runs through the codegen MCP server. BogDB is the graph layer Claude, GPT, and Llama agents can query directly — no adapter required, no glue code to maintain.
First-class index providers
A planner-integrated IExternalIndexProvider contract lets you plug entire access methods into BogDB's optimizer the same way Postgres lets you add custom access methods. Vector indexes, full-text engines, federated lookups, and the commercial SecureSearch provider all participate in planning and execution without forking the core.
Receipts
BogDB is validated test-by-test — against the upstream C++ engine where the semantics align, and against BogDB's own surface for everything new. The receipts:
| Surface | Status |
|---|---|
| Test suite | 1,803 passing · 0 failing · 0 skipped across engine and extensions |
| Golden query corpora | 52 / 52 green · 714 named golden queries |
| Optimizer rules | 12 transformation rules — TopK, FilterPushDown, LimitPushDown, AccHashJoin, JoinOrder, … |
| Scalar functions | 226 primary signatures — full upstream catalog plus BogDB extensions (upstream Kùzu: 111) |
| Window functions | 13 functions · full ROWS / RANGE / GROUPS frame clauses, all five bound types |
| GDS algorithms | 10 algorithms via CALL algo() YIELD * |
| Extension boundary | 10 public extension projects · SecureSearch held back as a commercial provider |
| Storage | Disk-backed columnar · MVCC · WAL with page-level recovery |
External index providers, first-class
Most graph databases that claim "extensibility" mean you can register a function. BogDB lets you register an entire access method. Implementations of IExternalIndexProvider participate in BogDB's planner and execution at the same level as built-in scans — the engine never has to know what index technology is behind them. The result is a clean separation: the engine handles parsing, planning, joins, projections, aggregation, and execution; the extension handles its own index, its own lookup semantics, and its own storage.
IExternalIndexProvider
The contract an extension implements to expose a custom index. The provider advertises which predicate shapes it can satisfy, returns a cost estimate for the planner, and yields physical scan execution on demand. Register one provider for an external vector store, another for an FTS engine, a third for commercial HMAC-tokenized secure search — they coexist and the planner picks the best match per query.
ExternalPredicatePlannerHook
A planner-time hook that runs during predicate placement. Registered providers inspect each predicate and may claim it — telling the optimizer "I can satisfy this faster than a full scan." Once claimed, the planner routes the predicate into an ExternalIndexScan instead of a default ScanNodeProperty plus PhysicalFilter pipeline. No core changes needed to onboard a new index technology.
ExternalIndexScan
The physical operator that delegates scan execution to the registered provider. Yields node or relationship IDs that match the claimed predicate, which then flow through the normal pipeline (joins, projections, aggregation, top-K) unchanged. Your extension only writes the part that's unique to your index; everything downstream is BogDB's existing machinery.
ExtensionLookupScan
A point-lookup specialization for predicate shapes that resolve to a single match or a small candidate set — secure equality lookups, hash-based dedup, primary-key probes against an external store. The planner picks this operator over ExternalIndexScan when an extension declares a predicate as a point lookup, so plans optimize for cardinality-one access instead of range scans.
This is the same architecture pattern Postgres pioneered with custom access methods. Anything that can describe a predicate shape and produce IDs can be a BogDB index — without modifying or forking the core engine.
A few things it can do
All in idiomatic .NET, no separate query process or out-of-proc service.
PageRank, in three lines
var r = conn.Query("CALL pagerank() YIELD *");
while (r.HasNext()) {
var row = r.GetNext();
Console.WriteLine($"node {row.GetString(0)} → rank {row.GetDouble(1):F6}");
}Window function over a graph projection
conn.Query(@"
MATCH (e:Employee)
RETURN e.dept, e.name, e.salary,
ROW_NUMBER() OVER (PARTITION BY e.dept ORDER BY e.salary DESC) AS rn
ORDER BY e.dept, rn");Variable-length paths, with materialized nodes and edges
conn.Query(@"
MATCH (a:Person)-[r*1..3]->(b:Person)
WHERE a.name = 'Alice'
RETURN a.name, length(r), nodes(r), rels(r)");Register an external index provider
public class MySecureIndex : IExternalIndexProvider
{
public string Name => "secure_lookup";
public bool CanSatisfy(PredicateShape shape) => shape.IsEquality;
public CostEstimate Estimate(PredicateShape shape) => new(rows: 1, cost: 1.0);
public IEnumerable<NodeId> Lookup(PredicateValue value) => _index.Find(value);
}
// Register at startup — planner and executor pick it up automatically
db.RegisterExternalIndexProvider(new MySecureIndex());Things to build with it
Each public sample is a working Blazor or console app in the BogDB repository.
SQL → Cypher Translator
A developer tool that converts SQL idioms to Cypher patterns. The fastest path for relational engineers learning graphs.
ExploreLLM Benchmarks
Benchmarks BogDB's query generation, retrieval, and graph-RAG performance across multiple LLM strategies.
ExploreSocial Graph
A classic social-network reference: people, follows, post-and-react. The "graph database 101" sample.
ExplorePackage Ecosystem
NuGet- and npm-style dependency-graph analysis: vulnerabilities, transitive impact, vendor concentration.
ExploreNutriGraph
A consumer-friendly food / ingredient / nutrient knowledge graph. Demonstrates richer modeling and traversal.
ExploreMonster Manual
A creature / ability / affinity browser in the classic tabletop-RPG style. Hierarchical and tag-based traversal, made fun.
ExploreWhere Beyond Ordinary builds revenue
The engine is free under Apache 2.0. We build the businesses on top: vertical accelerators, a secure-search index provider, FedRAMP-aligned hardening, managed and hosted deployments, and the full menu of support and integration services.
Our vertical accelerators are graph-backed application kits in the markets we know best: financial fraud detection, cyber compliance and CMMC posture, supply-chain risk, regulated healthcare, defense logistics, and tactical communications analysis. Each is a working Blazor reference application that integrates with your data sources via the BogDB external-index framework.
Commercial offerings
- SecureSearch index provider — HMAC-SHA256 tokenized equality with audit logging, persistence, and key-provider modes. Built for CUI and CMMC workflows.
- Vertical accelerators — financial fraud, cyber compliance, supply-chain risk, healthcare, defense logistics, tactical messaging analysis.
- Managed and hosted — we run BogDB for you with operational guarantees.
- Support and integration — direct engineer access, custom extension development, schema design, MCP integration.
- FedRAMP-aligned hardening — FIPS-mode binaries, controlled-environment deployment guidance.
A real migration, with AI on the team
BogDB is a three-month, AI-first migration of a real C++ database-engine surface to native .NET — no toy, no tutorial reskin, no single-tool experiment. Jacob Anderson led the engineering with four frontier models in the rotation: Claude (Anthropic), Codex (OpenAI), Gemini (Google), and Grok (xAI).
Each one earned its keep — drafting architecture documents, porting operators, generating tests, reasoning about optimizer rules, reviewing diffs, and pushing back when something didn't smell right. AI was on the team. The 1,803 passing tests, the 12-rule optimizer pipeline, the doubled scalar catalog, and the receipts above were earned the old-fashioned way — one regression at a time — by humans and AI working as collaborators, not as autocomplete.
This is also why we sell what we sell. If you want a team that can actually drive frontier models hard enough to ship a database engine, that's what Beyond Ordinary does for a living. The page above tells you how to reach us.
See BogDB powering a real graph workload — in 30 minutes.
BogDB is Apache 2.0 with the patent grant. Use it commercially, fork it, build on it. The core engine originated as a test-by-test parity port of the Kùzu C++ database (MIT, © 2022–2025 Kùzu Inc.) — preserved attribution, gratefully acknowledged. Everything new on top is Beyond Ordinary, contributed back under the same license.