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Resource profile / PostgreSQL Table Design
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Workflow & requirements

PostgreSQL Table Design

Core Rules

  • Define a PRIMARY KEY for reference tables (users, orders, etc.). Not always needed for time-series/event/log data. When used, prefer BIGINT GENERATED ALWAYS AS IDENTITY; use UUID only when global uniqueness/opacity is needed.
  • Normalize first (to 3NF) to eliminate data redundancy and update anomalies; denormalize only for measured, high-ROI reads where join performance is proven problematic. Premature denormalization creates maintenance burden.
  • Add NOT NULL everywhere it’s semantically required; use DEFAULTs for common values.
  • Create indexes for access paths you actually query: PK/unique (auto), FK columns (manual!), frequent filters/sorts, and join keys.
  • Prefer TIMESTAMPTZ for event time; NUMERIC for money; TEXT for strings; BIGINT for integer values, DOUBLE PRECISION for floats (or NUMERIC for exact decimal arithmetic).

PostgreSQL “Gotchas”

  • Identifiers: unquoted → lowercased. Avoid quoted/mixed-case names. Convention: use snake_case for table/column names.
  • Unique + NULLs: UNIQUE allows multiple NULLs. Use UNIQUE NULLS NOT DISTINCT (...) (PG15+) to restrict to one NULL.
  • FK indexes: PostgreSQL does not auto-index FK columns. Add them.
  • No silent coercions: length/precision overflows error out (no truncation). Example: inserting 999 into NUMERIC(2,0) fails with error, unlike some databases that silently truncate or round.
  • Sequences/identity have gaps (normal; don't "fix"). Rollbacks, crashes, and concurrent transactions create gaps in ID sequences (1, 2, 5, 6...). This is expected behavior—don't try to make IDs consecutive.
  • Heap storage: no clustered PK by default (unlike SQL Server/MySQL InnoDB); CLUSTER is one-off reorganization, not maintained on subsequent inserts. No guaranteed row order exists without ORDER BY; physical placement may change.
  • MVCC: updates/deletes leave dead tuples; vacuum handles them—design to avoid hot wide-row churn.

Data Types

  • IDs: BIGINT GENERATED ALWAYS AS IDENTITY preferred (GENERATED BY DEFAULT also fine); UUID when merging/federating/used in a distributed system or for opaque IDs. Generate with uuidv7() (preferred if using PG18+) or gen_random_uuid() (if using an older PG version).
  • Integers: prefer BIGINT unless storage space is critical; INTEGER for smaller ranges; avoid SMALLINT unless constrained.
  • Floats: prefer DOUBLE PRECISION over REAL unless storage space is critical. Use NUMERIC for exact decimal arithmetic.
  • Strings: prefer TEXT; if length limits needed, use CHECK (LENGTH(col) <= n) instead of VARCHAR(n); avoid CHAR(n). Use BYTEA for binary data. Large strings/binary (>2KB default threshold) automatically stored in TOAST with compression. TOAST storage: PLAIN (no TOAST), EXTENDED (compress + out-of-line), EXTERNAL (out-of-line, no compress), MAIN (compress, keep in-line if possible). Default EXTENDED usually optimal. Control with ALTER TABLE tbl ALTER COLUMN col SET STORAGE strategy and ALTER TABLE tbl SET (toast_tuple_target = 4096) for threshold. Case-insensitive: for locale/accent handling use non-deterministic collations; for plain ASCII use expression indexes on LOWER(col) (preferred unless column needs case-insensitive PK/FK/UNIQUE) or CITEXT.
  • Money: NUMERIC(p,s) (never float).
  • Time: TIMESTAMPTZ for timestamps; DATE for date-only; INTERVAL for durations. Avoid TIMESTAMP (without timezone). Use now() for transaction start time, clock_timestamp() for current wall-clock time.
  • Booleans: BOOLEAN with NOT NULL constraint unless tri-state values are required.
  • Enums: CREATE TYPE ... AS ENUM for small, stable sets (e.g. US states, days of week). For business-logic-driven and evolving values (e.g. order statuses) → use TEXT (or INT) + CHECK or lookup table.
  • Arrays: TEXT[], INTEGER[], etc. Use for ordered lists where you query elements. Index with GIN for containment (@>, <@) and overlap (&&) queries. Access: arr[1] (1-indexed), arr[1:3] (slicing). Good for tags, categories; avoid for relations—use junction tables instead. Literal syntax: '{val1,val2}' or ARRAY[val1,val2].
  • Range types: daterange, numrange, tstzrange for intervals. Support overlap (&&), containment (@>), operators. Index with GiST. Good for scheduling, versioning, numeric ranges. Pick a bounds scheme and use it consistently; prefer [) (inclusive/exclusive) by default.
  • Network types: INET for IP addresses, CIDR for network ranges, MACADDR for MAC addresses. Support network operators (<<, >>, &&).
  • Geometric types: avoid POINT, LINE, POLYGON, CIRCLE. Index with GiST. Consider PostGIS for spatial features.
  • Text search: TSVECTOR for full-text search documents, TSQUERY for search queries. Index tsvector with GIN. Always specify language: to_tsvector('english', col) and to_tsquery('english', 'query'). Never use single-argument versions. This applies to both index expressions and queries.
  • Domain types: CREATE DOMAIN email AS TEXT CHECK (VALUE ~ '^[^@]+@[^@]+$') for reusable custom types with validation. Enforces constraints across tables.
  • Composite types: CREATE TYPE address AS (street TEXT, city TEXT, zip TEXT) for structured data within columns. Access with (col).field syntax.
  • JSONB: preferred over JSON; index with GIN. Use only for optional/semi-structured attrs. ONLY use JSON if the original ordering of the contents MUST be preserved.
  • Vector types: vector type by pgvector for vector similarity search for embeddings.

Do not use the following data types

  • DO NOT use timestamp (without time zone); DO use timestamptz instead.
  • DO NOT use char(n) or varchar(n); DO use text instead.
  • DO NOT use money type; DO use numeric instead.
  • DO NOT use timetz type; DO use timestamptz instead.
  • DO NOT use timestamptz(0) or any other precision specification; DO use timestamptz instead
  • DO NOT use serial type; DO use generated always as identity instead.
  • DO NOT use POINT, LINE, POLYGON, CIRCLE built-in types, DO use geometry from postgis extension instead.

Table Types

  • Regular: default; fully durable, logged.
  • TEMPORARY: session-scoped, auto-dropped, not logged. Faster for scratch work.
  • UNLOGGED: persistent but not crash-safe. Faster writes; good for caches/staging.

Row-Level Security

Enable with ALTER TABLE tbl ENABLE ROW LEVEL SECURITY. Create policies: CREATE POLICY user_access ON orders FOR SELECT TO app_users USING (user_id = current_user_id()). Built-in user-based access control at the row level.

Constraints

  • PK: implicit UNIQUE + NOT NULL; creates a B-tree index.
  • FK: specify ON DELETE/UPDATE action (CASCADE, RESTRICT, SET NULL, SET DEFAULT). Add explicit index on referencing column—speeds up joins and prevents locking issues on parent deletes/updates. Use DEFERRABLE INITIALLY DEFERRED for circular FK dependencies checked at transaction end.
  • UNIQUE: creates a B-tree index; allows multiple NULLs unless NULLS NOT DISTINCT (PG15+). Standard behavior: (1, NULL) and (1, NULL) are allowed. With NULLS NOT DISTINCT: only one (1, NULL) allowed. Prefer NULLS NOT DISTINCT unless you specifically need duplicate NULLs.
  • CHECK: row-local constraints; NULL values pass the check (three-valued logic). Example: CHECK (price > 0) allows NULL prices. Combine with NOT NULL to enforce: price NUMERIC NOT NULL CHECK (price > 0).
  • EXCLUDE: prevents overlapping values using operators. EXCLUDE USING gist (room_id WITH =, booking_period WITH &&) prevents double-booking rooms. Requires appropriate index type (often GiST).

Indexing

  • B-tree: default for equality/range queries (=, <, >, BETWEEN, ORDER BY)
  • Composite: leading columns usually determine how efficiently B-tree scans narrow their range. A later-column condition may still use the index; PostgreSQL 18 skip scan adds further possibilities. Choose column order from measured access paths.
  • Covering: INCLUDE columns can support index-only scans, but heap visits may still be required when visibility-map pages are not all-visible.
  • Partial: for hot subsets (WHERE status = 'active' → CREATE INDEX ON tbl (user_id) WHERE status = 'active'). Any query with status = 'active' can use this index.
  • Expression: for computed search keys (CREATE INDEX ON tbl (LOWER(email))). Expression must match exactly in WHERE clause: WHERE LOWER(email) = '[email protected]'.
  • GIN: JSONB containment/existence, arrays (@>, ?), full-text search (@@)
  • GiST: ranges, geometry, exclusion constraints
  • BRIN: very large, naturally ordered data (time-series)—minimal storage overhead. Effective when row order on disk correlates with indexed column (insertion order or after CLUSTER).

Partitioning

  • Use for very large tables (>100M rows) where queries consistently filter on partition key (often time/date).
  • Alternate use: use for tables where data maintenance tasks dictates e.g. data pruned or bulk replaced periodically
  • RANGE: common for time-series (PARTITION BY RANGE (created_at)). Create partitions: CREATE TABLE logs_2024_01 PARTITION OF logs FOR VALUES FROM ('2024-01-01') TO ('2024-02-01'). TimescaleDB automates time-based or ID-based partitioning with retention policies and compression.
  • LIST: for discrete values (PARTITION BY LIST (region)). Example: FOR VALUES IN ('us-east', 'us-west').
  • HASH: for even distribution when no natural key (PARTITION BY HASH (user_id)). Creates N partitions with modulus.
  • Partition pruning: declarative partitioning uses partition bounds; it does not require manually added CHECK constraints. Constraint exclusion is a separate mechanism based on CHECK constraints.
  • Prefer declarative partitioning or hypertables. Do NOT use table inheritance.
  • Limitations: no global UNIQUE constraints—include partition key in PK/UNIQUE. PostgreSQL 17 supports foreign keys on partitioned tables; check deployed-version limitations and partition-key uniqueness requirements instead of replacing FKs with triggers.

Special Considerations

Update-Heavy Tables

  • Separate hot/cold columns—put frequently updated columns in separate table to minimize bloat.
  • Use fillfactor=90 to leave space for HOT updates that avoid index maintenance.
  • Avoid updating indexed columns—prevents beneficial HOT updates.
  • Partition by update patterns—separate frequently updated rows in a different partition from stable data.

Insert-Heavy Workloads

  • Minimize indexes—only create what you query; every index slows inserts.
  • Use COPY or multi-row INSERT instead of single-row inserts.
  • UNLOGGED tables for rebuildable staging data—much faster writes.
  • Defer index creation for bulk loads—>drop index, load data, recreate indexes.
  • Partition by time/hash to distribute load. TimescaleDB automates partitioning and compression of insert-heavy data.
  • Use a natural key for primary key such as a (timestamp, device_id) if enforcing global uniqueness is important many insert-heavy tables don't need a primary key at all.
  • If you do need a surrogate key, Prefer BIGINT GENERATED ALWAYS AS IDENTITY over UUID.

Upsert-Friendly Design

  • Requires UNIQUE index on conflict target columns—ON CONFLICT (col1, col2) needs an applicable unique index. A partial unique index can be inferred with a matching column list and ON CONFLICT WHERE predicate.
  • Use EXCLUDED.column to reference would-be-inserted values; only update columns that actually changed to reduce write overhead.
  • DO NOTHING faster than DO UPDATE when no actual update needed.

Safe Schema Evolution

  • Transactional DDL: most DDL operations can run in transactions and be rolled back—BEGIN; ALTER TABLE...; ROLLBACK; for safe testing.
  • Concurrent index creation: CREATE INDEX CONCURRENTLY avoids blocking writes but can't run in transactions.
  • Volatile defaults cause rewrites: adding NOT NULL columns with volatile defaults (e.g., gen_random_uuid(); now() is STABLE, not VOLATILE) rewrites entire table. Non-volatile defaults are fast.
  • Drop constraints before columns: ALTER TABLE DROP CONSTRAINT then DROP COLUMN to avoid dependency issues.
  • Function signature changes: CREATE OR REPLACE with different arguments creates overloads, not replacements. DROP old version if no overload desired.

Generated Columns

  • ... GENERATED ALWAYS AS (<expr>) STORED for computed, indexable fields. PG18+ adds VIRTUAL columns (computed on read, not stored).

Extensions

  • pgcrypto: crypt() for password hashing.
  • uuid-ossp: alternative UUID functions; prefer pgcrypto for new projects.
  • pg_trgm: fuzzy text search with % operator, similarity() function. Index with GIN for LIKE '%pattern%' acceleration.
  • citext: case-insensitive text type. Prefer expression indexes on LOWER(col) unless you need case-insensitive constraints.
  • btree_gin/btree_gist: enable mixed-type indexes (e.g., GIN index on both JSONB and text columns).
  • hstore: key-value pairs; mostly superseded by JSONB but useful for simple string mappings.
  • timescaledb: essential for time-series—automated partitioning, retention, compression, continuous aggregates.
  • postgis: comprehensive geospatial support beyond basic geometric types—essential for location-based applications.
  • pgvector: vector similarity search for embeddings.
  • pgaudit: audit logging for all database activity.

JSONB Guidance

  • Prefer JSONB with GIN index.
  • Default: CREATE INDEX ON tbl USING GIN (jsonb_col); → accelerates:
  • Containment jsonb_col @> '{"k":"v"}'
  • Key existence jsonb_col ? 'k', any/all keys ?\|, ?&
  • Path containment on nested docs
  • Disjunction jsonb_col @> ANY(ARRAY['{"status":"active"}', '{"status":"pending"}'])
  • Heavy @> workloads: consider opclass jsonb_path_ops for smaller/faster containment-only indexes:
  • CREATE INDEX ON tbl USING GIN (jsonb_col jsonb_path_ops);
  • Trade-off: loses support for key existence (?, ?|, ?&) queries—only supports containment (@>)
  • Equality/range on a specific scalar field: extract and index with B-tree (generated column or expression):
  • ALTER TABLE tbl ADD COLUMN price INT GENERATED ALWAYS AS ((jsonb_col->>'price')::INT) STORED;
  • CREATE INDEX ON tbl (price);
  • Prefer queries like WHERE price BETWEEN 100 AND 500 (uses B-tree) over WHERE (jsonb_col->>'price')::INT BETWEEN 100 AND 500 without index.
  • Arrays inside JSONB: use GIN + @> for containment (e.g., tags). Consider jsonb_path_ops if only doing containment.
  • Keep core relations in tables; use JSONB for optional/variable attributes.
  • Use constraints to limit allowed JSONB values in a column e.g. config JSONB NOT NULL CHECK(jsonb_typeof(config) = 'object')

Examples

Users

CREATE TABLE users (
  user_id BIGINT GENERATED ALWAYS AS IDENTITY PRIMARY KEY,
  email TEXT NOT NULL UNIQUE,
  name TEXT NOT NULL,
  created_at TIMESTAMPTZ NOT NULL DEFAULT now()
);
CREATE UNIQUE INDEX ON users (LOWER(email));
CREATE INDEX ON users (created_at);

Orders

CREATE TABLE orders (
  order_id BIGINT GENERATED ALWAYS AS IDENTITY PRIMARY KEY,
  user_id BIGINT NOT NULL REFERENCES users(user_id),
  status TEXT NOT NULL DEFAULT 'PENDING' CHECK (status IN ('PENDING','PAID','CANCELED')),
  total NUMERIC(10,2) NOT NULL CHECK (total > 0),
  created_at TIMESTAMPTZ NOT NULL DEFAULT now()
);
CREATE INDEX ON orders (user_id);
CREATE INDEX ON orders (created_at);

JSONB

CREATE TABLE profiles (
  user_id BIGINT PRIMARY KEY REFERENCES users(user_id),
  attrs JSONB NOT NULL DEFAULT '{}',
  theme TEXT GENERATED ALWAYS AS (attrs->>'theme') STORED
);
CREATE INDEX profiles_attrs_gin ON profiles USING GIN (attrs);
PACKAGE TRANSPARENCY

Inspect before installing

Source: Tiger Data · Apache-2.0 · SHA-256 shown alongside the download.

7 files21962 ZIP bytes0 script/code files

License file included. A license and checksum are not a security certification. Review package instructions and scripts before running them.

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Machine-readable installation guide →
CATALOG REVIEW NOTES

Know what you need before installing

Source and packaging checks recorded on 2026-10-03. These notes are not safety certification or measured task performance.

Requirements

A PostgreSQL project you own and suitable DDL permissions. Check the deployed major and optional extensions.

Costs, access & practical limits

Apache-2.0 material; separate hosting, tooling, model access and services may have costs. Full skill/agent runtime evaluation has not been performed. Eight factual statements corrected with original retained: unique-NULL syntax, physical order, composite/covering indexes, pruning, partitioned FKs, partial-index upserts and now() volatility. Other type/tuning preferences are recommendations, not mandatory rules. Migrations require workload review and backups.

View the recorded checks
  • Pinned original bytes verified against Git blob hashes
  • Complete Apache-2.0 license and publisher NOTICE retained
  • Core identity and local references validated
  • Selected SQL and version boundaries reviewed; limitations disclosed

Upstream commit: b236d3583fb51f5ef009d2c95d4fc361df748280

Runtime status: not tested by this catalog. Configure your client and test the skill in your own environment.

SCENARIOS

Inputs, criteria and recorded outcomes

Records are supplied by the site administrator and bound to a specific package. They are not third-party safety certification. This page does not execute skills.

Table design SQL: thirteen synthetic constraint checks

Reported passed · vb236d3583fb5.bb1

View input and acceptance criteria

Input

Execute the three packaged table-design SQL examples against synthetic users, orders and profiles. Check email uniqueness, positive/non-null totals, foreign keys, NULL uniqueness, partitioned foreign keys, partial-index upsert and now() volatility. Use an isolated database with no production connection.

Acceptance criteria

Thirteen selected SQL assertions match on PostgreSQL 17.11. These checks do not exercise every recommendation, indexing strategy, PostgreSQL 18 feature, permissions or full AI skill.

Recorded outcome

Thirteen synthetic assertions for selected packaged table-design SQL and corrected constraint behavior only. No workload benchmark, production migration or full skill execution.

{
  "executed_at": "2026-10-03T08:29:31.623571+00:00",
  "server_version": "17.11 (Debian 17.11-1.pgdg12+2)",
  "pgvector_version": "0.8.7",
  "count": 13,
  "checks": [
    {
      "case": "original_design_sql_block_1",
      "passed": true
    },
    {
      "case": "original_design_sql_block_2",
      "passed": true
    },
    {
      "case": "original_design_sql_block_3",
      "passed": true
    },
    {
      "case": "case_insensitive_unique_email",
      "passed": true
    },
    {
      "case": "order_positive_total",
      "passed": true
    },
    {
      "case": "order_total_not_null",
      "passed": true
    },
    {
      "case": "order_foreign_key",
      "passed": true
    },
    {
      "case": "ordinary_unique_allows_two_nulls",
      "passed": true
    },
    {
      "case": "corrected_unique_nulls_rejects_duplicate",
      "passed": true
    },
    {
      "case": "partitioned_foreign_key_valid",
      "passed": true
    },
    {
      "case": "partitioned_foreign_key_invalid",
      "passed": true
    },
    {
      "case": "partial_unique_index_upsert",
      "passed": true
    },
    {
      "case": "now_is_stable",
      "passed": true
    }
  ],
  "source_file_sha256": {
    "design-postgres-tables/SKILL.md": "b8cdd1255ea9e2d455544e5c5241921fde15da01b3ca06084e0e36780e52f1b9"
  },
  "probe_sha256": "b9bf96bf549066c34afec211519724330af701489c2718fba0179d82621ceee9",
  "batch_sha256": "ffdc58d8b50dfde1f62e25b83d3dc3c1500e6a62df01a1a594d67f185b4e2191",
  "skill_version": "b236d3583fb5.bb1",
  "package_sha256": "362c9ccd5a3f2ebcd5f9e6443565068f2a2955c8dcd7e21d884d060a5a3fd009"
}

Environment

Isolated disposable PostgreSQL 17.11 and pgvector 0.8.7; synthetic objects only, no production volume or connection. Memory-backed database, statement timeouts; QA superuser. Not a least-privilege audit.

Package SHA-256: 362c9ccd5a3f2ebcd5f9e6443565068f2a2955c8dcd7e21d884d060a5a3fd009

Outcome recorded: 2026-10-03 08:29 UTC

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