## Performance evidence update / 18 September 2026 MODALITY PERFORMANCE / EVIDENCE REVIEWED 18 SEPTEMBER 2026 Define the useful result. Measure the complete job. A modality-specific timing is not yet linked to this guide. There may be supporting engineering measurements in the internal archive. We are reconciling their workload, result quality and comparison conditions before presenting a public chart. A benchmark for an adjacent model does not establish this model’s performance. 01 Role-aware result correctness 02 Membership / intersection latency 03 Update amplification Include memory, storage, energy and hardware writes # Hypergraphs | 8DB Product reference. Reviewed 18 September 2026. Implementation and evaluation scope are stated below. Explore the models (https://8braid.com/modalities) / 8DB Hypergraphs Give a shared event its full cast. Represent a relationship that involves several participants and their roles, without reducing its meaning to a list of independent pairs. Explore the capabilities See a complete workload Group · relate · intersect Model / Hypergraphs Conceptual diagram [Diagram: hypergraphs representation: conceptual diagram] One relationship spans multiple participants. Overlapping groups show shared membership. Capabilities What changes Input to value Alternatives Performance Adoption Related articles Reference Start with the operations your question needs. Typed n-ary facts with participant roles Participant lookup Role and type intersections Documented product scope, reviewed 17 September 2026. The underlying build and deployment must be qualified for your application. Native n-ary representation does not imply a dedicated operator for every hypergraph pattern. A property graph can also model an observation as a node with role-labelled relationships. Connected native models Keep the next question within reach. A native n-ary fact retains its own identity and participants. This can simplify asking about the whole observation and its evidence without rebuilding the intended grouping from unrelated pairwise edges. [Diagram: tables representation: conceptual diagram] Tables Familiar rows. More context within reach. Filter · sort · project Explore model ↗ (https://8braid.com/modalities/tables) [Diagram: time series representation: conceptual diagram] Time series Keep the meaning in every observation. Observe · window · analyze Explore model ↗ (https://8braid.com/modalities/time-series) [Diagram: documents representation: conceptual diagram] Documents Keep the source behind the answer. Structure · search · trace Explore model ↗ (https://8braid.com/modalities/documents) These connections show the models involved in the application design. Compare the supported combination and full workflow with a realistic alternative. Input → usable value / interactive design example Explain which observations support a laboratory result 0 1 Identify participants → 0 2 Keep one fact → 0 3 Match the group → 0 4 Attach evidence → 0 5 Explain the result → [Diagram: tables representation: conceptual diagram] Step 1 / Tables Receive an observation and its participant identities Rows share a structure. A query selects the fields and records relevant to the question. Next: Keep one fact Conceptual application workflow. Qualify the supported operations, external tools, protection and persistence for the complete path. These diagrams are explanatory, not measured results. Read the complete workflow and comparison scope Receive an observation and its participant identities Store the roles as one n-ary fact Find matching sample, method and instrument combinations Join the associated measurement and source document Return a result with its full observation context Measure the work of creating, updating and recovering the same grouped fact, including role constraints and source retrieval. Avoid comparing one native lookup with an artificially inefficient graph query. Compare a realistic alternative. A property graph provides a realistic alternative through explicit observation nodes and relationships. Compare the representation, validation burden and query path rather than claiming that pairwise stores cannot express the fact. Neo4j property graph model (https://neo4j.com/docs/getting-started/appendix/graphdb-concepts/) Compare equivalent outputs and required guarantees, including the simplest single-product alternative where one exists. A specialist may remain the better fit when its operators, ecosystem or operational maturity are decisive. Combining native models becomes valuable when your actual question crosses them. Performance & resources Measure the work that delivers the answer. Role/participant correctness; n-ary lookup latency by cardinality; ingestion/update cost; index/storage size; complete evidence-response latency. This draft does not assign a new speed ratio or score to this modality. Existing measurements and source leads are retained in the evidence programme; a qualified public result must identify the particular operation and path tested. Explore the published benchmark evidence (https://8braid.com/benchmarks) What belongs inside the timer and resource budget? For input-to-value testing, declare the input state and the consumer-ready output first. Include parsing, derivation, storage/protection, index readiness, querying, result assembly and delivery as applicable. Identify amortized setup and any work deferred past the finish line. Report database-stage and full-job results separately. Do not add unrelated medians or p95 values, or multiply component speedups into a claimed workflow result. Energy needs measured joules; reduced handoffs alone do not establish a saving. Choose the path that fits your deployment. Verify the supported API/SDK, data format, persistence and indexing behaviour for the release you plan to use. Match the operation-by-modality protection profile and device qualification to the workload. Post-quantum protection (https://8braid.com/pqc) · Plan a workload evaluation (https://8braid.com/build) Related articles Take the next step into the thinking. Mechanism & application 8DB | Native Multimodal Data: Connect the Dots Across Graphs, Maps and Time Series (https://8braid.com/journal/modality-is-a-projection) Explore the ideas and implementation context behind this capability. Mechanism & application Give Your AI the Evidence Behind the Answer (https://8braid.com/journal/the-database-is-part-of-the-model) Explore the ideas and implementation context behind this capability. Reference / Reviewed 17 September 2026 Readable, shareable and traceable. This reference explains 8DB’s public modality description (https://8braid.com/modalities#explore) with an explicit workload and selection criteria. It is a documentary review, not fresh execution of every operator or platform. Public sources: 8DB modality scope (https://8braid.com/modalities) ; Neo4j property graph model (https://neo4j.com/docs/getting-started/appendix/graphdb-concepts/) ; the related articles above. Internal source leads and outstanding release checks remain in the editorial record. Download this reference (https://8braid.com/modality-reference/hypergraphs.md) Evaluate the question your application needs to answer. Bring the data shapes, input state, expected output and the systems you use today. Define a comparison around that complete job. Discuss your workload (https://8braid.com/build)