PostgreSQL

DE//AGENT currently lists 4 resources under PostgreSQL: 2 projects, 1 skill, 1 template. Everything below is derived from the live registry — counts, capabilities, verification state and security posture come from the curated records, never from marketing copy.

Documented learning objectives across these resources:

• Read a plan bottom-up and name the expensive node — via SQL Query Plan Explainer
• Detect cardinality misestimation from stale statistics — via SQL Query Plan Explainer
• Decide between an index, a rewrite, or a stats refresh — via SQL Query Plan Explainer
• Configure a logical replication slot safely — via Postgres → CDC → Kafka → Lakehouse
• Order events by LSN and dedupe before merging — via Postgres → CDC → Kafka → Lakehouse
• Handle tombstones without losing history — via Postgres → CDC → Kafka → Lakehouse
• Layer staging/intermediate/marts — via dbt → warehouse → tests → docs
• Write tests that protect the grain — via dbt → warehouse → tests → docs

1 more objectives live on the individual resource pages.

These resources map to stages: Python + SQL (1), Cloud (1), Warehousing (1), Streaming (1). Follow the four-phase roadmap to place this topic inside a progression instead of learning it in isolation.

Every entry, its shape and its trust state — sorted by the registry's composite score. This table is the honest version of a marketing comparison: no sponsored placements, no unverifiable claims.

How scores are computed: source quality score.

Highest composite score first:

1. SQL Query Plan Explainer score 38.5 — intermediate
2. Local Docker Data Stack score 34.1 — beginner
3. Postgres → CDC → Kafka → Lakehouse score 33.65 — advanced

Scores rank provenance, completeness and trust — read how verification works before adopting anything.

Start here if you're new: Local Docker Data Stack, dbt → warehouse → tests → docs.

Reach for these with production experience: Postgres → CDC → Kafka → Lakehouse.

Security-flagged entries: SQL Query Plan Explainer (1 flag), Local Docker Data Stack (2 flags), Postgres → CDC → Kafka → Lakehouse (4 flags), dbt → warehouse → tests → docs (4 flags). Flags mean the record declares capabilities like credential use or write access — read the security posture on each page before connecting.

• SQL Query Plan Explainer — Reads EXPLAIN / EXPLAIN ANALYZE output and explains scans, joins, spills and estimated-vs-actual row skew, then proposes the single highest-impact change. details
• Local Docker Data Stack — A docker-compose stack (Postgres, Kafka, MinIO, Spark, and a DuckDB CLI) for developing and testing pipelines entirely offline. details
• Postgres → CDC → Kafka → Lakehouse — Capture changes from Postgres with Debezium, stream through Kafka, and merge into a lakehouse table with correct ordering, deletes and replay safety. details
• dbt → warehouse → tests → docs — Transform raw landed data into a tested, documented star schema with dbt, and gate every change on data-aware CI. details

Real install commands from the registry — read the source before running any of them:

npx de-agent-platform add sql-query-plan-explainer

SQL Query Plan Explainer — review first

amp template new de-agent/docker-local-stack ./local

Local Docker Data Stack — review first

Official source: PostgreSQL (license: PostgreSQL) — start there for the canonical documentation, then come back for the vetted registry entries.

Adjacent topics: DuckDB (2 shared), Apache Spark (2 shared), Apache Kafka (2 shared).

Study path: the roadmap places this topic in a progression · the scoring model explains the numbers · the trust rule catalog shows every security check these entries passed through.