Turn a missing reading into a useful next step.
Request missing evidence, wait for late data, or recognize an interval when no reading was expected.
Respond to missing readings →8DB / The omnimodal database
Search the text. Follow the relationships. Understand the signal. Bring more of your question into the same database.
Conceptual model map. Explore each guide for supported operations.
Start with the useful result
A question rarely stops at one data model.
Explore how several models contribute to a useful result.
Connect relevant passages to their sources, relationships and context.
Follow dependencies, preserve shared context and inspect the supporting records.
Bring time, place and uncertainty into the same investigation.
Illustrative workflows. Each guide includes alternatives, evaluation criteria and the scope still to qualify. Prefer to start with a representation? Browse all 17 models ↓
From a native operation to a useful decision
Storing a structure is the beginning. Its operations determine which questions your application can answer.
Request missing evidence, wait for late data, or recognize an interval when no reading was expected.
Respond to missing readings →An answer can keep the same number while its justification changes. Find the dependent work that needs review.
Trace changed evidence →A candidate may offer more benefit at more cost. Preserve the alternatives instead of hiding that choice inside one score.
Compare meaningful alternatives →Distinct implementation examples, with their scope explained at each destination. See the evidence and scope →
01 / Find your data model
Select a model for a visual introduction.
Open its guide for operations, comparisons and evidence.
17 model guides
Store it. Find it. Retrieve it.
Follow how things connect.
Understand change and uncertainty.
Work with location and geometry.
Explore content and dimensions.
Preserve the shape of the problem.
Composite applications connect several representations. They are a separate route into the library.
02 / From input to useful answer
A familiar question often needs several kinds of data. Follow the work from its source to the answer.
Personal media / Illustrative workflow
Similarity finds candidates. Time and place narrow the answer.
Import-to-searchable time · relevance · memory · stored bytes
Design example, not an executed combined benchmark. Include metadata extraction, embedding generation and permissions in the complete job.
Multimodal performance / Evidence reviewed 18 September 2026
Same-host synthetic shipping fixture; same four logical CPUs per server; 20 timed requests each, including HTTP and decoded JSON. Exact ships and timestamps checked. Custom Rust composition versus SurrealQL. Preparation excluded; resident-memory paths without durable completion or authentication. This measures the combination, not an isolated graph, spatial or time-series operation.
Read the results, comparison and methods →8DB used about 74% less resident memory at the recorded post-query checkpoint. Client and OS cache excluded; this is not a minimum device requirement. Energy and SSD wear were not measured.
Record build-time and serving memory separately, original and derived stored bytes, measured joules per completed job, and physical writes including indexing, compaction and recovery. A smaller representation does not by itself prove lower energy or longer device life.
Match correctness, freshness, durability and protection across alternatives. Encryption, authorization, adapters, network setup and output delivery belong in the complete-job comparison wherever required. No universal zero-overhead claim follows from these results.
03 / The buying decision
Multi-model databases such as SurrealDB already combine familiar representations. Compare what you can actually do with them, what information survives and what your team still has to assemble.
See SurrealDB’s documented models