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v2.0 Release Note

Document version: v2.0

Position: the additional-capability whitepaper after v1.0. v2.0 continues the Foggy semantic-layer engine story without deprecating v1.0 or replacing its foundational syntax references.

Implementation policy: this document focuses on Java-engine capabilities that are implemented and signed off. Planned, prompt-only, and unsigned experimental behavior is not described as stable functionality.

Core changes

v1.0 established the foundation: TM/QM semantic modeling, JSON Query DSL, MCP tools, permission governance, query evidence, and Compose analysis.

v2.0 advances governed query into governed complex analysis:

  • Java MCP can recalibrate a route and redispatch instead of continuing an expired plan.
  • Query processing can emit non-blocking trace correlation for catalog, planner, tool call, validator, and result stages.
  • DSL_CTE provides staged analysis with governed aggregation, derivation, windows, post-filtering, ordering, and limited cross-result bridges.
  • Relation result-stage expressions are a signed formula set for ratios, differences, delta ratios, labels, and ordered buckets.
  • Memory Grid provides bounded handles, lifecycle, resource limits, and fail-closed guards for secondary analysis.
  • Pivot enters the signed Java-engine scope with tree axes, axis windows, drilldown contracts, and database date/weekday corrections.
  • Experience Recipe becomes a minimal registry lookup with namespace, tenant, permission, owner, and active-state filtering.

Capability summary

Areav2.0 additionBoundary
Java MCP orchestrationcalibrated-route redispatch and non-blocking trace correlationNot an autonomous analyst; validator, policy, and fail-closed rules remain required
DSL_CTE staged analysisaggregate, derive, window, postSlice, orderBy, and governed bridge templatesNo arbitrary SQL CTE or physical-table join
Governed expressionsratio, difference, delta ratio, absolute delta ratio, threshold label, ordered bucket, alias DAG, signed rankingNo arbitrary functions, CASE, physical fields, or free expression language
Memory Gridbounded result handle, resolver, lifecycle, limits, cross-model alignmentNo unbounded detail, arbitrary DuckDB API, full outer/multi-key join, or durable backend promise
Pivottree axis, axis window/domain selection, cascade drilldown, weekday dialect parityNo unsigned shape, arbitrary interactive expansion, or complete BI pivot product
Experience Recipeexact registry lookup, governance filtering, publish evidence, signature-verifier SPINot a recipe marketplace, vector search, admin console, or trust root
Multi-database evidenceSQLite, MySQL8, PostgreSQL pivot/DSL_CTE evidence and SQL Server weekday parityNot a complete SQL Server Maven profile release gate

State vocabulary

StateMeaningDocumentation rule
Signed offCovered by Java runtime, validator, fixture, CI, or acceptance evidenceMay be described as a v2.0 stable capability
Narrow contract availableWorks only within a signed template, model, shape, or dialect evidenceAlways state the use case and rejection boundary
Follow-up directionPlanned or evaluated, but not a stable Runtime promiseKeep it in exclusions or future direction

Relationship to v1.0

v2.0 keeps v1.0 principles:

  • The LLM does not access a bare database schema directly.
  • Requests enter through semantic models, structured DSL, and tools.
  • The engine owns permissions, field validation, dialect translation, and execution evidence.
  • Prompt instructions are not a security boundary.

The new contracts increase analytical power without relaxing governance. The more complex the analysis, the more important signed contracts, test evidence, and fail-closed behavior become.

Not included in v2.0

  • Free physical SQL execution.
  • Arbitrary Semantic SQL, CTE, or expression language.
  • Generic cross-model joins, generic funnels, generic attribution, or arbitrary period comparisons.
  • A complete BI product, report designer, SQL notebook, or customer-facing AI analytics workbench.
  • A complete SQL Server release gate, production durable Memory Grid backend, full Recipe marketplace, or governed vector search.
  • Full parity for all new capabilities between Python and Java.