design-postgres-tables

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# 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**: 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**: 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.

From HelixDevelopment/agent, MIT.

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