Lakehouse-native graph engine with git-style workflows https://omnigraph.dev
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Ragnor Comerford 5cfae9acc1
docs(rfc-013): latency = (serial_hops + ops/concurrency)·RTT — concurrency-cap correction + Lance-metadata comparison (#292)
* feat(engine): compact the internal __manifest/_graph_commits tables in optimize

`optimize` iterated node/edge catalog tables only, so the two internal system
tables (`__manifest`, `_graph_commits`) accumulated one fragment per commit and
were never compacted -- making every write's metadata scan O(fragments), which
grows forever on a long-lived graph (RFC-013 step 2).

`optimize_all_tables` now also compacts both internal tables via a new
`compact_internal_table`. They are not catalog-tracked (readers open them at
their latest Lance HEAD), so it is a much simpler path than `optimize_one_table`:
compact in place, no manifest publish (nothing to publish to), no recovery
sidecar (a single atomic Lance commit -- no HEAD-before-publish gap), and no
optimize_indices (they carry no Lance index, only object_id's unenforced-PK
metadata). No application lock: Lance's compact_files auto-retries its Rewrite
against any concurrent writer (the canonical LanceDB pattern; Rewrite vs Append
is compatible, vs Update a retryable same-fragment conflict Lance rebases), and a
coordinator refresh afterwards makes the warm handle observe the compacted HEAD.

Compacts both tables even though Phase 7 (iss-991) will later fold _graph_commits
into __manifest -- a one-call throwaway for the full interim win; __manifest
compaction is also the prerequisite for Phase 7's graph_head contention. Cleanup
(version GC) of the internal tables is deliberately NOT included here: it needs
the Q8 cleanup-resurrection watermark first (deferred).

maintenance.rs: optimize now returns 6 stats (4 data + 2 internal); adds
optimize_compacts_internal_tables (sheds fragments, leaks no recovery sidecar,
graph coherent for reads + strict writes after).

* test(engine): un-ignore the internal-table scan LOCK (step 2 acceptance)

`internal_table_scans_are_flat_in_history` was the RED, #[ignore]'d acceptance
gate staged in PR #288. With internal-table compaction landed, a write's
__manifest/_graph_commits scan is flat in commit-history depth on a compacted
graph (measured __manifest 4->2, _graph_commits 7->3 across depth 10->100, vs the
pre-step-2 RED 34->214 / 29->207). The test now compacts at each depth before
measuring and runs green every-PR.

* docs: RFC-013 step 2 internal-table compaction landed

- invariants.md: close the compaction half of the read-path-rederivation known
  gap (optimize now compacts the internal tables; cleanup half still deferred).
- maintenance.md: optimize covers __manifest/_graph_commits (no publish, no
  sidecar); not yet in cleanup.
- rfc-013 §9: split step 2 into 2a (compaction, landed) and 2b (cleanup + Q8
  watermark, deferred — debated; MTT-overlap + hot-path liability).
- testing.md: the internal-table LOCK is now green every-PR.

* fix(engine): guard absent _graph_commits + always compact internal tables

Addresses PR #291 review findings:

- Greptile (P1): optimize unconditionally opened `_graph_commits` for compaction,
  but a graph can validly have none (the coordinator opens it as `Option`, gated on
  `storage.exists`, for graphs predating the commit graph). `Dataset::open` on the
  absent table errored and failed the whole optimize. Guard the `_graph_commits`
  compaction with the same `storage_adapter().exists()` check the coordinator uses;
  `__manifest` always exists so it stays unguarded. Regression test
  `optimize_tolerates_absent_graph_commits_table` (empty graph so no publish
  recreates the table before the guard).

- Cursor (low): the `table_tasks.is_empty()` early return skipped internal-table
  compaction for a schema with no node/edge types. Removed it so the internal
  tables are compacted regardless of the data-table set.

- Codex (auto-cleanup, P1): documented — `compact_files` commits with a default
  `CommitConfig` (no skip_auto_cleanup) and `CompactionOptions` exposes no override,
  so on a graph storing an *on* auto_cleanup config the commit would fire version
  GC. Both internal tables are created with `auto_cleanup: None`, so new graphs are
  safe; the only exposure is pre-fix upgraded graphs, identical to the existing
  data-table optimize path, with step 2b's watermark as the comprehensive guard.
  Added a comment in `compact_internal_table` recording this.

* docs(rfc-013): serial-hop correction — wall-clock is the ~110-hop backbone, not op count

Latency-slope measurement on the deployed edge binary (f6d2cc03, steps 1+3a
landed; rustfs + per-op latency proxy, depth 1..85) shows wall-clock is set by a
~110-hop SERIAL backbone that is depth-invariant. Total ops grow +~7/depth but
PARALLELIZE (parallelism 1->6), so the depth term adds little wall-clock.

- New §0(c): the serial-hop vs total-op finding + branch-op backbones
  (create ~77, delete ~87, branch-write ~258/1777-ops/21s floor = fork-on-first-write).
- §2.4: correct the '1720->198 ops => 258s->30s' op-count->wall-clock conversion.
- §5.1: promote serial-hop/num_stages to the PRIMARY latency LOCK; op-count
  flatness demoted to a cost/compute-floor gate.
- §9 step 2: reprioritized as Phase-7 prerequisite + compute-floor/space, NOT
  the wall-clock fix; step 3b (parallel capture-once WriteTxn) is the headline
  latency lever; branch-write moved under step 3b + fork seam.
- Summary: serial-backbone correction up front.

Vindicates the §3/§4.1 design; corrects the op-count latency framing.

* docs(rfc-013): concurrency-cap correction + Lance-metadata comparison

Fold in two measured findings from the deployed edge binary (f6d2cc03) on
rustfs behind a latency+concurrency proxy:

- §0(d): concurrency-cap A/B. Under unlimited concurrency the internal-table
  scan parallelizes (backbone ~110); under an R2-realistic cap (8) it serializes
  and an UNCOMPACTED graph runs away (per-write ops 1273->3505, wall 6->16s),
  while #291's internal compaction cuts it ~6x and bounds it (137->1 frag). The
  latency model is (serial_hops + ops/effective_concurrency)*RTT + compute.
- Reframe step 2 across Summary/§2.4/§9: NOT de-ranked — on R2 (capped) it is a
  primary latency lever + the anti-runaway fix + Phase-7 prereq. The earlier
  'step 2 is parallel, irrelevant to latency' was an unlimited-concurrency
  artifact. Deployed f6d2cc03 optimize is node/edge-only; #291 (undeployed) is
  the prod win.
- §5.1: the cost-gate ThrottledStore must cap concurrency AND inject latency;
  assert serial_hops flat AND ops flat in history.
- §2.3 + §8: Lance/LanceDB comparison from 7.0.0 source — Lance metadata is a
  single-file per-version manifest read O(1) (latest_version_hint), pruned by
  default; omnigraph's __manifest-as-Lance-dataset scan is self-inflicted by the
  cross-table-atomicity choice. Adds explicit defense of Lance-dataset __manifest
  (MTT seam) vs a flat-file CAS'd manifest (cheaper, off the MTT path).

Design (§3/§4.1) unchanged and vindicated; corrections are measurement framing,
step sizing, and one design-choice that was implicit.
2026-06-21 21:54:59 +02:00
.cargo Raise LANCE_MEM_POOL_SIZE to 1 GB in .cargo/config.toml 2026-04-19 22:27:49 +03:00
.context Investigate Lance MergeInsertBuilder CAS granularity (MR-766 prereq) 2026-04-28 23:30:17 +00:00
.github write-path cost gate + opener bypass (#288) 2026-06-20 13:31:15 +02:00
assets docs(readme): drop em-dashes, Cursor→Codex, rename agent section (#274) 2026-06-17 02:36:14 +03:00
crates (feat): compact the internal manifest/commit-graph tables in optimize (#291) 2026-06-21 16:38:20 +02:00
docker fix(cluster): stop cluster-apply crash-loops from the recovery-sidecar trap (#284) 2026-06-19 03:34:15 +03:00
docs docs(rfc-013): latency = (serial_hops + ops/concurrency)·RTT — concurrency-cap correction + Lance-metadata comparison (#292) 2026-06-21 21:54:59 +02:00
scripts docs: onboarding-first README + in-repo agent skill + drop RustFS script (#257) 2026-06-16 11:48:13 +02:00
skills/omnigraph docs: onboarding-first README + in-repo agent skill + drop RustFS script (#257) 2026-06-16 11:48:13 +02:00
.dockerignore feat(docker): cluster-mode entrypoint and the CLI in the image 2026-06-10 22:44:54 +03:00
.gitignore release: v0.5.0 (#115) 2026-05-23 13:59:42 +01:00
AGENTS.md release: v0.7.1 (#290) 2026-06-19 23:12:44 +03:00
Cargo.lock release: v0.7.1 (#290) 2026-06-19 23:12:44 +03:00
Cargo.toml build(deps): bump Lance 6.0.1 → 7.0.0 (correct-by-design substrate alignment) (#229) 2026-06-14 20:42:24 +02:00
CLAUDE.md Add AGENTS.md as canonical agent guide; symlink CLAUDE.md to it 2026-04-28 23:10:09 +02:00
CODE_OF_CONDUCT.md Initial public Omnigraph repository 2026-04-10 20:49:41 +03:00
CONTRIBUTING.md chore: remove CODEOWNERS chassis and the code-owner review gate 2026-06-18 02:55:27 +03:00
Dockerfile feat(docker): cluster-mode entrypoint and the CLI in the image 2026-06-10 22:44:54 +03:00
GOVERNANCE.md chore: remove CODEOWNERS chassis and the code-owner review gate 2026-06-18 02:55:27 +03:00
LICENSE Initial public Omnigraph repository 2026-04-10 20:49:41 +03:00
og-cheet-sheet.md feat: inline query strings in CLI and HTTP server (#110) 2026-05-29 13:41:54 +02:00
omnigraph.example.yaml example config: use graphs / cli.graph, matching the MR-603 rename 2026-04-18 23:40:35 +03:00
openapi.json docs(user): coherence cleanup aligned with 0.7.1 (#293) 2026-06-21 00:02:34 +03:00
README.md docs(readme): drop em-dashes, Cursor→Codex, rename agent section (#274) 2026-06-17 02:36:14 +03:00
rust-toolchain.toml Initial public Omnigraph repository 2026-04-10 20:49:41 +03:00
SECURITY.md Initial public Omnigraph repository 2026-04-10 20:49:41 +03:00

OMNIGRAPH

Lakehouse graph database for context assembly & multi-agent coordination
Multimodal retrieval · Git-style branching · object-storage native

Quickstart  ·  Docs  ·  Cookbooks  ·  CLI

License: MIT crates.io Rust


Omnigraph is the operational state and coordination layer for fleets of agents.
Run it as a server, declared as code; hundreds of agents operate and enrich the graph on parallel isolated branches, and every change is reviewed and merged safely.

Key capabilities

Capability What it gives you
Declared as code A cluster.yaml declares graphs, schemas, stored queries, embedding providers, and policies; cluster apply converges it and omnigraph-server brings every graph online at /graphs/{id}/….
Built for fleets of agents Hundreds of agents enrich the graph on parallel isolated branches; changes are reviewed and merged safely, Git-style, across the whole graph.
Multimodal retrieval Graph traversal + vector ANN + full-text + Reciprocal Rank Fusion in one query runtime, for context assembly.
Security as code Cedar policy enforced server-side on every mutation, per-graph and server-wide; bearer auth; actor/audit tracking.
Runs on your infrastructure Any S3-compatible object store: on-prem via RustFS / MinIO, or AWS S3 / R2 / GCS. VPC, on-prem, hybrid; your data never leaves your store.
Open, versioned storage Lance columnar format: branchable, time-travelable, with native blob-as-data (docs, images, video).

What you can build

Use case What it's for
Company brain Org knowledge unified into one graph every agent can query
Agentic memory Durable, versioned memory: a branch per agent or per task, merged on review
Context graph Decision traces and codified tribal knowledge for retrieval
Dev graph Issues & dependency model that coding agents read and write
R&D / ML data layer Experiments and trials written into branches, versioned for training & eval

Install

curl -fsSL https://raw.githubusercontent.com/ModernRelay/omnigraph/main/scripts/install.sh | bash

This installs omnigraph (CLI) and omnigraph-server into ~/.local/bin from published release binaries. Or with Homebrew:

brew tap ModernRelay/tap
brew install ModernRelay/tap/omnigraph

Set it up with an AI agent

Omnigraph is built to be run by coding agents. Two ways in:

Teach your agent the playbook. This repo ships the omnigraph agent skill: the operational playbook covering cluster mode, the two config surfaces, schema evolution, query linting, data writes, branches, Cedar policy, and the common gotchas.

npx skills add ModernRelay/omnigraph@omnigraph

Or have an agent set it up from scratch. Paste this into Claude Code, Codex, or any agent that can read a URL and run a shell command:

Help me set up Omnigraph

1. Read the docs at https://github.com/ModernRelay/omnigraph, starting with
   docs/user/clusters/index.md, then docs/user/deployment.md.
2. Skim the starter graphs and seed data in the cookbooks:
   https://github.com/ModernRelay/omnigraph-cookbooks
3. Ask me what I want to build (company brain, agent memory, dev graph,
   research / R&D layer, …). Then stand up a cluster for it, load a little
   data, and run a query so I can see it working.

For ready-to-run graphs with real seed data (company brain, VC operating system, pharma & industry intel), ModernRelay/omnigraph-cookbooks is the fastest way to see Omnigraph shaped to a real domain.

Deploy

A deployment is a cluster: a multigraph config directory that declares its graphs, schemas, stored queries, and policies as code. You manage it Terraform-style: cluster plan previews the diff, cluster apply converges it. omnigraph-server then boots from the cluster and brings every graph online at /graphs/{id}/…, each behind its own policy.

1. Declare the cluster.

company-brain/
├── cluster.yaml
├── people.pg          # schema for the "knowledge" graph
├── queries/           # stored queries: the .gq files ARE the declaration
│   └── people.gq
└── base.policy.yaml   # a Cedar policy bundle
# cluster.yaml
version: 1
metadata:
  name: company-brain
storage: s3://company/clusters/company-brain   # ledger, catalog, and graph data live here
graphs:
  knowledge:
    schema: people.pg
    queries: queries/                          # every `query <name>` in queries/*.gq registers
policies:
  base:
    file: base.policy.yaml
    applies_to: [knowledge]                    # graph-bound; use [cluster] for server-level

2. Stand up your object store. On-prem, run RustFS (or MinIO); Omnigraph writes Lance to it over the standard S3 API. In the cloud, point the same AWS_* env at S3 / R2 / GCS instead.

3. Converge and run. apply creates each graph, applies its schema, and publishes queries and policies into the content-addressed catalog. It is idempotent; re-running is always safe.

omnigraph cluster validate   # parse + typecheck everything
omnigraph cluster plan       # preview what apply would do
omnigraph cluster apply      # converge

# Boot the server from the cluster dir; storage resolves through cluster.yaml
omnigraph-server --cluster company-brain --bind 0.0.0.0:8080

See the cluster guide for the day-2 loop (edit → plan → apply → restart), approval gates for destructive changes, drift inspection, and recovery; the deployment guide for containers, AWS/Railway, auth, and the full AWS_* contract.

Query and mutate

Set a default server and graph once in ~/.omnigraph/config.yaml, and the everyday commands stay short. Stored queries and mutations run by name:

omnigraph query  search_docs --params '{"q":"AI safety"}'
omnigraph mutate add_person  --params '{"name":"Mina"}'

# Branch, review, merge across the whole graph; agents write in isolation
omnigraph branch create --from main agent/ingest-42
omnigraph branch merge  agent/ingest-42 --into main

An alias is shorter still: bind a server, graph, and stored query to one name, then omnigraph alias triage runs it. For an ad-hoc target, any command still takes --server <name|url> --graph <id> (or --store <uri> for a local graph). See the CLI reference.

Security & governance

  • Engine-wide enforcement: every write path goes through the same Cedar gate, so the HTTP server, the CLI, and the embedded SDK obey identical rules.
  • Declared in the cluster: a policy bundle is bound to graphs (or the whole server) via policies:applies_to.
  • Scoped: rules apply per graph, per branch, or server-wide.
  • No plaintext tokens: bearer tokens are hashed at startup and compared in constant time.
  • Forge-proof identity: the actor is resolved server-side from the token; clients can't set it.

See the policy guide.

Clients & SDKs

Client Use it for Where
TypeScript SDK typed access from Node / TS @modernrelay/omnigraph · source
MCP server bridge Omnigraph to LLM hosts (Claude, Codex, …) @modernrelay/omnigraph-mcp
HTTP / OpenAPI any language, the wire contract the server's OpenAPI spec
Python SDK typed access from Python coming soon

Both npm packages are versioned in lockstep with omnigraph-server.

Local quick test (no server)

1-min setup to try it: an embedded, local file-backed graph (no server, no object store). For dev and experiments; production is the deployed cluster above.

cat > schema.pg <<'PG'
node Signal  { slug: String @key, title: String }
node Pattern { slug: String @key, name: String }
edge Indicates: Signal -> Pattern
PG
printf '%s\n' \
  '{"type":"Signal","data":{"slug":"s1","title":"OSS model adoption surging"}}' \
  '{"type":"Pattern","data":{"slug":"p1","name":"adoption"}}' \
  '{"edge":"Indicates","from":"s1","to":"p1"}' > data.jsonl

omnigraph init  --schema schema.pg ./graph.omni
omnigraph load  --data data.jsonl --mode overwrite --store ./graph.omni

# "What pattern does signal s1 indicate?"
omnigraph query --store ./graph.omni \
  -e 'query indicates() { match { $s: Signal { slug: "s1" }  $s indicates $p } return { $p.name } }'
# → adoption

Docs

Build And Test

cargo build --workspace
cargo test  --workspace

Notes:

  • Rust stable toolchain, edition 2024
  • CI runs cargo test --workspace --locked
  • Full CI and some local test flows require protobuf-compiler
  • S3 integration tests expect an S3-compatible endpoint such as RustFS

Workspace Crates

  • crates/omnigraph-compiler: shared schema/query parser, typechecker, catalog, and IR lowering (zero Lance dependency)
  • crates/omnigraph (package omnigraph-engine): storage/runtime, branching, merge, change detection, query execution, and embeddings
  • crates/omnigraph-policy: Cedar policy compilation and enforcement
  • crates/omnigraph-api-types: shared HTTP wire DTOs used by both the server and the CLI
  • crates/omnigraph-cluster: cluster config validation, planning, and apply (the control plane)
  • crates/omnigraph-server: Axum HTTP server, cluster-first, runs N graphs under /graphs/{id}/…
  • crates/omnigraph-cli: CLI for graph lifecycle, query/mutate, branch/commit/merge, schema/lint, snapshot/export, cluster control, policy/queries, profiles, and maintenance

Contributing

Please open an issue, spec, or design discussion before sending large code changes. Design feedback and concrete problem statements are the fastest way to collaborate on the roadmap.

Community

Join the Omnigraph Slack community to ask questions, share feedback, and follow development.