## 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 Bound / uncertainty correctness 02 Propagation latency 03 Representation bytes Include memory, storage, energy and hardware writes # Uncertainty & evidence | 8DB Product reference. Reviewed 18 September 2026. Implementation and evaluation scope are stated below. Explore the models (https://8braid.com/modalities) / 8DB Uncertainty & evidence Let an answer carry what is known. Represent bounded and uncertain values so applications can distinguish an observation from an estimate and preserve its limits. Explore the capabilities See a complete workload Bound · qualify · explain Model / Uncertainty Conceptual diagram [Diagram: values representation: conceptual diagram] An exact point and a bounded interval express different knowledge. The interval is not a probability distribution. Capabilities What changes Input to value Alternatives Performance Adoption Related articles Reference Start with the operations your question needs. Recorded typed distribution representations Set and multiset values Measures and collection building blocks Documented product scope, reviewed 17 September 2026. The underlying build and deployment must be qualified for your application. Recorded types do not establish arbitrary statistical inference, calibrated uncertainty or every set operator. Verify the actual validation and query contract for the chosen value type. Connected native models Keep the next question within reach. The representation matters: a distribution retains parameters, a multiset retains repeated membership and a typed measure has a declared interpretation. These building blocks can support richer native data shapes. [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: tables representation: conceptual diagram] Tables Familiar rows. More context within reach. Filter · sort · project Explore model ↗ (https://8braid.com/modalities/tables) [Diagram: graphs representation: conceptual diagram] Graphs Follow the relationship to a better answer. Connect · traverse · follow Explore model ↗ (https://8braid.com/modalities/graphs) 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 Compare uncertain observations without collapsing them too early 0 1 Receive the values → 0 2 Keep their types → 0 3 Apply the operation → 0 4 Connect the source → 0 5 Retain the assumptions → [Diagram: values representation: conceptual diagram] Step 1 / Uncertainty Receive values with units and declared distribution or collection meaning An exact point and a bounded interval express different knowledge. The interval is not a probability distribution. Next: Keep their types 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 values with units and declared distribution or collection meaning Validate the supported typed representation Apply the qualified comparison or collection operations Connect the result to its time and source records Present a result that retains its assumptions Match the mathematical semantics before timing operations. Comparing a richer uncertainty representation with a single point estimate would change the output contract. Compare a realistic alternative. General databases and analytical libraries can encode distributions and collections. The evaluation should identify which semantics are built in, which need custom code and how those values compose with other models. Xarray analysis context (https://8braid.com/modalities/https://docs.xarray.dev/en/stable/getting-started-guide/why-xarray) 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. Type/parameter and multiplicity fidelity; operation correctness; serialization size; operator latency; reproducibility and complete response cost. 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 | Eight Explanations. How Can a New Kind of Database Help You Tell Them Apart? (https://8braid.com/journal/when-the-answer-is-more-than-yes-or-no) Explore the ideas and implementation context behind this capability. 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. 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) ; Xarray analysis context (https://8braid.com/modalities/https://docs.xarray.dev/en/stable/getting-started-guide/why-xarray) ; the related articles above. Internal source leads and outstanding release checks remain in the editorial record. Download this reference (https://8braid.com/modality-reference/values.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)