name: postgresql-table-design
description: Design a PostgreSQL-specific schema. Covers best-practices, data types, indexing, constraints, performance patterns, and advanced features
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. Row order on disk is insertion order unless explicitly clustered.
- 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:
POINT, LINE, POLYGON, CIRCLE for 2D spatial data. Index with GiST. Consider PostGIS for advanced 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.
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: order matters—index used if equality on leftmost prefix (
WHERE a = ? AND b > ? uses index on (a,b), but WHERE b = ? does not). Put most selective/frequently filtered columns first.
- Covering:
CREATE INDEX ON tbl (id) INCLUDE (name, email) - includes non-key columns for index-only scans without visiting table.
- 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) = 'user@example.com'.
- 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.
- Constraint exclusion: requires
CHECK constraints on partitions for query planner to prune. Auto-created for declarative partitioning (PG10+).
- Prefer declarative partitioning or hypertables. Do NOT use table inheritance.
- Limitations: no global UNIQUE constraints—include partition key in PK/UNIQUE. FKs from partitioned tables not supported; use 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 exact matching unique index (partial indexes don't work).
- 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., now(), gen_random_uuid()) 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);
Raw SKILL.md
---
name: postgresql
description:
---
---
name: postgresql-table-design
description: Design a PostgreSQL-specific schema. Covers best-practices, data types, indexing, constraints, performance patterns, and advanced features
---
# 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 **DEFAULT**s 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. Row order on disk is insertion order unless explicitly clustered.
- **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**: `POINT`, `LINE`, `POLYGON`, `CIRCLE` for 2D spatial data. Index with **GiST**. Consider **PostGIS** for advanced 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.
## 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**: order matters—index used if equality on leftmost prefix (`WHERE a = ? AND b > ?` uses index on `(a,b)`, but `WHERE b = ?` does not). Put most selective/frequently filtered columns first.
- **Covering**: `CREATE INDEX ON tbl (id) INCLUDE (name, email)` - includes non-key columns for index-only scans without visiting table.
- **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) = 'user@example.com'`.
- **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.
- **Constraint exclusion**: requires `CHECK` constraints on partitions for query planner to prune. Auto-created for declarative partitioning (PG10+).
- Prefer declarative partitioning or hypertables. Do NOT use table inheritance.
- **Limitations**: no global UNIQUE constraints—include partition key in PK/UNIQUE. FKs from partitioned tables not supported; use 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 exact matching unique index (partial indexes don't work).
- **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., `now()`, `gen_random_uuid()`) 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
```sql
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
```sql
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
```sql
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);
```