converged-database-lab: module 02 — Converged vs. Multi-Model (article 2 companion)

labs/converged-database-lab/README.md

@@ -93,8 +93,8 @@ All modules run against one deterministically seeded domain. Seeds use an LCG (s
 
 | # | Slug | Status | Proofs | Assertions | Links |
 |---|------|--------|--------|------------|-------|
-| 01 | `what-is-a-converged-database` | Live | 4 | 14 | [README](modules/01-what-is-a-converged-database/README.md) · article link lands at publish |
-| 02 | `converged-vs-multi-model` | Arrives with its article | — | — | — |
+| 01 | `what-is-a-converged-database` | Live | 5 | 20 | [README](modules/01-what-is-a-converged-database/README.md) · [article](https://blogs.oracle.com/developers/what-is-a-converged-database-definition-five-tests-and-ai-use-cases) |
+| 02 | `converged-vs-multi-model` | Live | 3 | 18 | [README](modules/02-converged-vs-multi-model/README.md) · article link lands at publish |
 | 03 | `vector-db-vs-converged` | Arrives with its article | — | — | — |
 | 04 | `ai-agents-enterprise-data` | Arrives with its article | — | — | — |
 | 05 | `json-graph-vector-relational-one-db` | Arrives with its article | — | — | — |

labs/converged-database-lab/docker/Dockerfile.oracle

@@ -13,27 +13,6 @@ RUN printf '[mongodb-org-8.0]\nname=MongoDB Repository\nbaseurl=https://repo.mon
  && microdnf install -y mongodb-mongosh \
  && microdnf clean all
 
-# Bake Oracle's prebuilt augmented all-MiniLM-L12-v2 ONNX model into the image so
-# every fresh build (and CI) loads identical in-DB embeddings deterministically —
-# no network dependency at init time. This is the official model published by
-# Oracle Machine Learning: the 26ai docs "ONNX Pipeline Models: Text Embedding"
-# page redirects (/pls/topic/lookup?...&id=oml_ai_models_object_storage) to the
-# OML-ai-models object-storage bucket whose index lists this exact URL. The zip
-# (~122.6 MB) unpacks to all_MiniLM_L12_v2.onnx (~133.3 MB, 384-dim output),
-# loaded by docker/init/08-vector-model.sql via DBMS_VECTOR.LOAD_ONNX_MODEL.
-# Placed AFTER the ORDS + mongosh layers so their (slow) cache layers are reused
-# when only the model layer changes. Fails the build loudly if the URL stops
-# resolving rather than baking a broken image.
-ARG MINILM_URL=https://adwc4pm.objectstorage.us-ashburn-1.oci.customer-oci.com/p/TtH6hL2y25EypZ0-rrczRZ1aXp7v1ONbRBfCiT-BDBN8WLKQ3lgyW6RxCfIFLdA6/n/adwc4pm/b/OML-ai-models/o/all_MiniLM_L12_v2_augmented.zip
-RUN microdnf install -y unzip \
- && microdnf clean all \
- && mkdir -p /opt/oracle/models \
- && curl -fsSL -o /tmp/minilm.zip "$MINILM_URL" \
- && unzip -o /tmp/minilm.zip -d /opt/oracle/models \
- && test -s /opt/oracle/models/all_MiniLM_L12_v2.onnx \
- && rm -f /tmp/minilm.zip \
- && chown -R oracle:oinstall /opt/oracle/models
-
 COPY init/ /container-entrypoint-initdb.d/
 
 COPY scripts/entrypoint.sh /opt/oracle/scripts/entrypoint.sh

labs/converged-database-lab/modules/02-converged-vs-multi-model/README.md

@@ -0,0 +1,138 @@
+# Module 02 — Converged vs Multi-Model
+
+Three runnable proofs for leaf article 2's core claims ("multi-model is a
+storage claim; converged is a guarantees claim"). Every script executes
+against the live lab container and emits machine-checkable assertions
+(`ASSERT:<name>:PASS|FAIL`). No screenshots, no trust-me — run them yourself.
+
+---
+
+## Proof 1: `scripts/01-survey-challenge.sql`
+
+**Article claim: the academic literature's canonical multi-model query runs as
+one standard SQL statement.** Lu & Holubová's ACM Computing Surveys survey of
+multi-model databases (52(3) Art. 55, 2019) opens with a running example
+(their Fig. 1): relational customers (Mary, credit 5000; John, 3000; William,
+2000), a "knows" social graph, and orders as JSON documents — challenge query:
+*"Return all product_no which are ordered by a friend of a customer whose
+credit_limit>3000"*, published result `['2724f','3424g']`. The survey solves
+it in ArangoDB AQL and OrientDB SQL, each a proprietary language on its own
+engine. This script recreates the dataset as module-local tables plus a SQL
+property graph, then answers the query in **one statement**: `GRAPH_TABLE`
+(SQL/PGQ, ISO/IEC 9075-16) walks the knows-graph, `JSON_TABLE` (SQL/JSON,
+SQL:2016) unnests the order lines, a relational predicate filters on
+`credit_limit` — and an assertion checks the result set equals the survey's
+published answer **exactly**. `EXPLAIN PLAN` then shows graph, document, and
+relational access costed as ordinary row sources in a single plan tree.
+
+**Dataset note:** the survey publishes the customers, the query, and the
+result, but not the complete knows-edge topology or full order documents. The
+script constructs the minimal dataset consistent with the survey's published
+inputs and published result (Mary knows John and William; John's order
+contains product `2724f`, William's contains `3424g`); `Order_no`,
+`Product_Name`, and `Price` values are constructed placeholders in the
+survey's document shape.
+
+**DDL exception:** this script intentionally performs DDL, and DDL
+autocommits — the harness rollback cannot undo it. Cleanup is therefore
+explicit and asserted: every module-local object (`smm_` prefix) is dropped
+before the script ends, an idempotence guard at the top clears leftovers from
+interrupted runs, and the transactional `EXPLAIN PLAN` rows are deleted before
+the autocommitting drops so `plan_table` is left unchanged too.
+
+Expected assertions:
+
+```
+ASSERT:survey-result-exact:PASS
+ASSERT:plan-captured:PASS
+ASSERT:plan-spans-graph:PASS
+ASSERT:plan-spans-relational:PASS
+ASSERT:plan-spans-document:PASS
+ASSERT:plan-evaluates-json:PASS
+ASSERT:one-plan-tree:PASS
+ASSERT:smm-tables-dropped:PASS
+ASSERT:smm-graph-dropped:PASS
+ASSERT:plan-table-clean:PASS
+```
+
+## Proof 2: `scripts/02-one-enforcement-domain.js`
+
+**Article claim: one enforcement domain — the same constraint guards every
+API.** The shared domain declares `CHECK (qty > 0)` on `order_items`. The
+script pushes `qty: -1` through the MongoDB document API (an `updateOne` on
+the `order_dv` duality view) and gets a `MongoServerError` carrying
+`ORA-02290` (check-constraint violated); it then submits the same violation as
+a SQL `UPDATE` through the `$sql` aggregation stage on the same connection and
+gets the same `ORA-02290`. Document and rows verified unchanged after both
+attempts. The constraint lives in the engine, beneath every surface — there is
+no per-API validation layer to drift.
+
+**Error-text note:** the exact `MongoServerError` message format (ORA-42692
+wrapping ORA-02290 on the document path; bare ORA-02290 via `$sql`) is
+observed behavior on Oracle AI Database 26ai Free as of June 2026, not a
+documented contract. Assertions match only the documented element — the
+ORA-02290 code.
+
+Expected assertions:
+
+```
+ASSERT:doc-read:PASS
+ASSERT:mongo-api-rejected:PASS
+ASSERT:doc-unchanged:PASS
+ASSERT:sql-update-rejected:PASS
+ASSERT:final-state-unchanged:PASS
+```
+
+## Proof 3: `scripts/03-read-after-write-search.sql`
+
+**Article claim: transactional read-after-write text search.** The script
+inserts a support ticket containing a unique marker token, COMMITs, and
+immediately finds it with `CONTAINS` — then deletes it, COMMITs, and
+immediately does not. Search visibility arrives with the commit, in the same
+engine, with no separate search process, change stream, or refresh interval.
+The lab's `ticket_text_idx` is created with `PARAMETERS ('SYNC (ON COMMIT)')`
+(`docker/init/05-text-vector.sql`), so the text index syncs inside the
+committing transaction.
+
+**Commit exception:** this script intentionally COMMITs (read-after-write can
+only be shown across a real commit boundary), so the harness rollback does not
+apply; explicit, asserted cleanup restores the domain. It is reseed-safe —
+`ticket_id` is identity-generated and the probe row is addressed only by its
+unique subject/marker, never a fixed id.
+
+Expected assertions:
+
+```
+ASSERT:contains-finds-committed-write:PASS
+ASSERT:contains-after-cleanup:PASS
+ASSERT:probe-rows-gone:PASS
+```
+
+## Cross-reference: the one-optimizer proof lives in module 01
+
+The companion article also leans on **one cost-based plan spanning graph,
+document, vector, and relational** access. That evidence is module 01's
+[`05-one-plan.sql`](../01-what-is-a-converged-database/scripts/05-one-plan.sql)
+(`EXPLAIN PLAN` over the shared domain: `GRAPH_TABLE` + JSON predicate +
+`VECTOR_DISTANCE` + relational joins in one plan tree). Leaf article 2 quotes
+that proof; this module deliberately does not duplicate it — proof 1's plan
+assertions here cover the survey statement specifically.
+
+---
+
+## Run It Yourself
+
+```bash
+docker compose up -d --build oracle
+pip install -r validator/requirements.txt
+python validator/run.py
+```
+
+The validator runs every script (modules 01 and 02) and exits 0 only if all
+assertions pass.
+
+**These proofs leave the seeded domain unchanged.** Two scripts in this module
+are documented exceptions to the rollback contract — proof 1 performs DDL
+(autocommits) and proof 3 COMMITs — so both clean up explicitly and assert the
+cleanup, which keeps the validator repeatable: run it any number of times with
+identical results.