Schema-aware query
Your schemaknows the way.
Import your ElectroDB or DDB Toolbox entities and query with the access patterns you already defined. Keys resolve into real composite strings, filters know their types, and results pivot across entities.
Your code is the source of truth. Point Dynomatic at the entity definitions in your codebase. It parses and normalizes them, maps each entity to its DynamoDB table, and turns the schema into a working query surface. No schema files? Dynomatic can infer the model from your data →
Pick a pattern, not an index. Access patterns from your schema drive the builder: key inputs lay themselves out, the resolved composite key sits under every field, and a missing key is flagged before you run.
Pivot across entities without starting over. Any linked value in the results lists every access pattern that can query it, across every entity in your schema. Each hop lands in the trail, so you always know how you got there.
The query surface, up close
Select the TypeScript files that define your ElectroDB or DDB Toolbox entities. Detection, parsing, and normalization are automatic.
Every imported entity is associated with a real DynamoDB table, so the builder knows how your code relates to your data.
Patterns from your schema, listed by name with their index. Primary and sort key inputs build themselves from the entity definition.
Filter fields know their data types and valid operators. A projection picker trims results to the attributes you need.
Inspect the table and index the generated command targets before it runs. Exactly what Dynomatic sends to AWS, in the open.
Schema files change. Re-scan to pick up the new definitions and keep the builder in sync with your codebase.