Heartwood vs Cognee — provable records vs graph/ontology memory
TL;DR
Cognee combines relational, vector, and graph stores to turn source data into searchable, connected memory, with tenant/dataset-level permissions and documented audit logging; it leads on graph and ontology depth and has a longer public history than Heartwood. Heartwood's difference is record-level cryptographic proof — signed memories, policy-before-ranking, key-destruction erasure — that you re-execute yourself.
At-a-glance table
| Axis | Heartwood Memory | Cognee |
|---|---|---|
| Governance granularity | Per individual memory record | Tenant roles + direct dataset-level read/write/delete grants |
| Provenance signing | Per-record Ed25519, re-verified at read (opt-in strict enforcement) | Not evaluated in public docs (document-level metadata/provenance) |
| Tamper-evident audit | Hash-chained audit log | Not evaluated in public docs (Cloud lists audit logging) |
| Policy-before-ranking | Yes | Not evaluated in public docs (results limited to accessible datasets) |
| Erasure / RTBF | Crypto-shred + key-destruction receipt | Item/dataset/all deletion of graph/vector/relational data, with caveats (no cryptographic proof) |
| Tenant isolation | Yes | Yes — complete data isolation; workspace = tenant |
| Interface | Python library + governed MCP server | Python API, HTTP API, CLI, MCP tools |
| Deployment | Self-hosted, embedded | Local/embedded, self-hosted Docker, managed Cloud, Enterprise BYO cloud |
| License | Source-available (BSL 1.1); 0.1.x MIT | Apache-2.0 OSS engine; Cloud + Enterprise separate |
| Pricing | Free / Team $349·mo / Pro $6,000·yr / Enterprise Let’s talk | Free ($0, 1 workspace/1M tokens) / Standard $2.50 per 1M tokens + $5/workspace / Enterprise custom |
| Best-for | Record-level, re-executable proof | Graph/ontology-centered memory pipelines |
Competitor pricing verified 2026-08-07 against Cognee's primary pricing documentation; other Cognee facts verified 2026-07-15. “Not evaluated in public docs” = not found in Cognee's primary documentation on the date checked; it is not a claim the feature is absent. Each date is a point-in-time snapshot, not a continuing assurance.
Comparison by dimension
Governance
Cognee governs at the dataset level with access controls and telemetry, and it leads on the knowledge-graph and ontology model. Heartwood governs at the record level: per-memory signatures, policy-before-ranking, and crypto-shred erasure. If cognee is further along on graph depth, Heartwood's lane is record-level proof.
Deletion
Cognee deletion removes graph, vector, and relational data (with raw-file/shared-node caveats); Heartwood adds a per-subject key-destruction receipt.
Who Cognee is best for
Teams building graph/ontology-centered memory pipelines with OSS or managed deployment.
Who Heartwood is best for
Regulated teams that need per-record, re-executable proof.
Can Heartwood run underneath Cognee?
As the governed store behind shape-compatible memory calls (example contract, not an official integration).
See the governed-memory modelFAQ
Does Cognee have access control?
Yes — tenant roles plus direct dataset-level read/write/delete grants. Heartwood's difference is per-record, re-executable proof.
Is Cognee open source?
Cognee's engine is Apache-2.0; hosted Cloud and Enterprise are separate.