SQL foundations, ACID, and constraints
Use real PostgreSQL constraints, parameterized SQL, and a rollback to see where data integrity actually lives.
Timeline
Understanding: SQL foundations, ACID, and constraints
You can read this chapter before running the experiment. Then return to the live trace and match each concept to a real event.
A database is not a large JSON file or passive storage. It checks rules, coordinates competing changes, and chooses how to retrieve rows. A good schema does not merely store data; it prevents states that are impossible for the business.
The relational model describes entities as tables, identifies rows with keys, and encodes relationships and valid values with constraints. PostgreSQL parses declarative SQL, evaluates possible plans, chooses one from statistics, and executes it inside a transaction. ACID describes atomicity, consistency, isolation, and durability. Consistency is a joint responsibility of the schema and business logic, not automatic database magic.
Terms used in this experiment
Understand the words first, then the execution order.
Relational model
A data model built from tables, rows, columns, keys, and constraints. SQL describes a desired result rather than a row-by-row algorithm.
Constraint
A rule checked by the database during writes: NOT NULL, CHECK, UNIQUE, PRIMARY KEY, or FOREIGN KEY.
Invariant
A condition that must remain true, such as a positive order amount or an order referencing an existing customer.
ACID
Atomicity, Consistency, Isolation, and Durability: properties of reliable transactional changes.
WAL
Write-Ahead Log: changes are logged before corresponding data pages to support recovery.
SQLSTATE
A stable machine-readable PostgreSQL error code. Applications should not parse localized error text.
What happens step by step
Each step maps to an observable runtime state.
- 01Model the invariants
Define entities, identity, required values, valid states, and relationships before choosing an ORM.
- 02Encode rules in DDL
PRIMARY KEY, UNIQUE, CHECK, and FOREIGN KEY protect data regardless of which service performs the write.
- 03Send values as parameters
The driver sends SQL and values separately; $1 does not turn user input into SQL syntax.
- 04Open a transaction
BEGIN creates one unit of work whose changes are committed or rolled back together.
- 05Receive a structured error
A CHECK violation returns SQLSTATE 23514, which the application maps to a domain result.
- 06Verify rollback
The runtime inserts a row inside a transaction, rolls back, and confirms that persistent state did not change.
Where the result needs context
These details explain why similar code can sometimes produce a different trace.
Consistency is not automatic business logic
The database enforces declared constraints but cannot guess missing invariants. ACID does not create a rule that the schema and transaction never expressed.
NULL uses three-valued logic
Comparing to NULL yields UNKNOWN, so use IS NULL. CHECK also accepts UNKNOWN unless NOT NULL is declared separately.
Types are part of the model
numeric is appropriate for exact decimal arithmetic; timestamptz stores an instant rather than a display time zone.
A migration is a production operation
ALTER TABLE can acquire a strong lock or rewrite a table. Evaluate data size, lock level, rollout, and rollback.
A pool is not a transaction
Every query in one transaction must use the same checked-out client. Independent pool.query calls can use different connections.
First understand which parts of Node participate in execution.
Then remove instrumentation and focus on the central mechanism.
Finally match the model to the code that produces the live trace.
A minimal model without instrumentation
const client = await pool.connect();
try {
await client.query('BEGIN');
const order = await client.query(
'INSERT INTO orders(customer_id, amount) VALUES ($1, $2) RETURNING id',
[customerId, amount],
);
await client.query('COMMIT');
return order.rows[0];
} catch (error) {
await client.query('ROLLBACK');
throw error;
} finally {
client.release();
}The complete code executed by the scenario
This is not an alternative example: these are the functions and files used by the Run button.
The source is generated from the real server function. Scenarios using a child process or Worker include every participating file.
import { randomUUID } from 'node:crypto';
import { performance } from 'node:perf_hooks';
import pg from 'pg';
const { Pool } = pg;
const STATEMENT_TIMEOUT_MS = 8_000;
const CONNECTION_TIMEOUT_MS = 1_500;
function databaseUrl() {
return process.env.DATABASE_URL?.trim() || null;
}
function safeIdentifier(prefix) {
return `${prefix}_${randomUUID().replaceAll('-', '').slice(0, 12)}`;
}
function planReport(result) {
const raw = result.rows[0]['QUERY PLAN'];
const report = Array.isArray(raw) ? raw[0] : JSON.parse(raw)[0];
const nodes = [];
function visit(node, depth = 0) {
nodes.push({
depth,
type: node['Node Type'],
relation: node['Relation Name'] ?? null,
index: node['Index Name'] ?? null,
estimatedRows: node['Plan Rows'],
actualRows: node['Actual Rows'],
loops: node['Actual Loops'],
});
for (const child of node.Plans ?? []) visit(child, depth + 1);
}
visit(report.Plan);
return {
nodes,
executionMs: Number(report['Execution Time'] ?? 0),
planningMs: Number(report['Planning Time'] ?? 0),
};
}
function planLine(plan) {
return plan.nodes
.map((node) => {
const target = node.index ?? node.relation;
return `${' '.repeat(node.depth)}${node.type}${target ? ` [${target}]` : ''}`;
})
.join(' → ');
}
async function configureClient(client) {
await client.query(`SET statement_timeout = '${STATEMENT_TIMEOUT_MS}ms'`);
await client.query(
`SET idle_in_transaction_session_timeout = '${STATEMENT_TIMEOUT_MS}ms'`,
);
await client.query("SET lock_timeout = '2500ms'");
}
async function rollbackQuietly(client) {
if (!client) return;
try {
await client.query('ROLLBACK');
} catch {
// The client may not currently be in a transaction.
}
}
async function withDatabaseLab(emit, run) {
const connectionString = databaseUrl();
if (!connectionString) {
emit(
'postgres',
'skip',
'PostgreSQL не подключён: задайте DATABASE_URL или запустите проект через Docker Compose',
);
return false;
}
const pool = new Pool({
connectionString,
max: 4,
connectionTimeoutMillis: CONNECTION_TIMEOUT_MS,
idleTimeoutMillis: 5_000,
allowExitOnIdle: true,
application_name: 'node-loop-lab',
});
const schema = safeIdentifier('node_loop_lab');
try {
const versionResult = await pool.query(
"SELECT current_setting('server_version') AS version",
);
emit(
'postgres',
'connect',
`Подключён PostgreSQL ${versionResult.rows[0].version}; создаём изолированную схему ${schema}`,
);
await pool.query(`CREATE SCHEMA ${schema}`);
await run({ pool, schema });
return true;
} catch (error) {
const safeMessage =
error?.code === 'ECONNREFUSED'
? 'соединение отклонено'
: error?.code
? `SQLSTATE ${error.code}`
: 'ошибка подключения';
emit('postgres', 'error', `Сценарий PostgreSQL остановлен: ${safeMessage}`);
return false;
} finally {
try {
await pool.query(`DROP SCHEMA IF EXISTS ${schema} CASCADE`);
emit('cleanup', 'drop', 'Учебная схема удалена; постоянные данные не создавались');
} catch {
// Connection failures can make cleanup impossible; the schema name is unique
// and contains no user data.
}
await pool.end().catch(() => {});
}
}
export async function databaseConstraintsAndAcid(emit) {
await withDatabaseLab(emit, async ({ pool, schema }) => {
const client = await pool.connect();
try {
await configureClient(client);
emit(
'ddl',
'schema',
'Создаём PRIMARY KEY, UNIQUE, CHECK и FOREIGN KEY как правила целостности внутри БД',
);
await client.query(`
CREATE TABLE ${schema}.customers (
id bigint GENERATED ALWAYS AS IDENTITY PRIMARY KEY,
email text NOT NULL UNIQUE,
name text NOT NULL CHECK (char_length(name) >= 2)
);
CREATE TABLE ${schema}.orders (
id bigint GENERATED ALWAYS AS IDENTITY PRIMARY KEY,
customer_id bigint NOT NULL
REFERENCES ${schema}.customers(id) ON DELETE RESTRICT,
amount numeric(12, 2) NOT NULL CHECK (amount > 0),
status text NOT NULL DEFAULT 'new'
CHECK (status IN ('new', 'paid', 'cancelled'))
);
`);
const customer = await client.query(
`INSERT INTO ${schema}.customers (email, name)
VALUES ($1, $2)
RETURNING id`,
['learner@example.com', 'Learner'],
);
emit(
'query',
'parameters',
'Параметры $1/$2 переданы отдельно от SQL: значения не становятся частью синтаксиса запроса',
);
try {
await client.query(
`INSERT INTO ${schema}.orders (customer_id, amount)
VALUES ($1, $2)`,
[customer.rows[0].id, -50],
);
} catch (error) {
emit(
'constraint',
'check',
`CHECK отклонил отрицательную сумму: SQLSTATE ${error.code}`,
);
}
await client.query('BEGIN');
await client.query(
`INSERT INTO ${schema}.orders (customer_id, amount, status)
VALUES ($1, $2, $3)`,
[customer.rows[0].id, 1250, 'paid'],
);
const inside = await client.query(
`SELECT count(*)::int AS count FROM ${schema}.orders`,
);
await client.query('ROLLBACK');
const after = await client.query(
`SELECT count(*)::int AS count FROM ${schema}.orders`,
);
emit(
'transaction',
'rollback',
`Внутри транзакции строк=${inside.rows[0].count}; после ROLLBACK строк=${after.rows[0].count}`,
);
emit(
'acid',
'model',
'ACID: constraints поддерживают consistency, транзакция даёт atomicity, WAL/disk — durability, а isolation управляет видимостью параллельных изменений',
);
} finally {
await rollbackQuietly(client);
client.release();
}
});
}
export async function databaseIndexesAndExplain(emit) {
await withDatabaseLab(emit, async ({ pool, schema }) => {
const client = await pool.connect();
try {
await configureClient(client);
emit(
'dataset',
'seed',
'Создаём 40 000 событий с коррелированным временем, tenant_id, status и массивом tags',
);
await client.query(`
CREATE TABLE ${schema}.events (
id bigint GENERATED ALWAYS AS IDENTITY PRIMARY KEY,
tenant_id integer NOT NULL,
created_at timestamptz NOT NULL,
status text NOT NULL,
tags text[] NOT NULL
);
INSERT INTO ${schema}.events (tenant_id, created_at, status, tags)
SELECT
(g % 100) + 1,
now() - (g * interval '1 second'),
CASE WHEN g % 5 = 0 THEN 'failed' ELSE 'processed' END,
ARRAY[
CASE WHEN g % 3 = 0 THEN 'api' ELSE 'worker' END,
CASE WHEN g % 7 = 0 THEN 'priority' ELSE 'normal' END
]
FROM generate_series(1, 40000) AS g;
ANALYZE ${schema}.events;
`);
const query = `
SELECT id, created_at, status
FROM ${schema}.events
WHERE tenant_id = 37
AND created_at >= now() - interval '6 hours'
ORDER BY created_at DESC
`;
const before = planReport(
await client.query(`EXPLAIN (ANALYZE, BUFFERS, FORMAT JSON) ${query}`),
);
emit(
'planner',
'before-index',
`До составного индекса: ${planLine(before)}; execution=${before.executionMs.toFixed(2)} ms`,
);
await client.query(`
CREATE INDEX events_tenant_created_btree
ON ${schema}.events USING btree (tenant_id, created_at DESC)
INCLUDE (status);
CREATE INDEX events_status_hash
ON ${schema}.events USING hash (status);
CREATE INDEX events_created_brin
ON ${schema}.events USING brin (created_at);
CREATE INDEX events_tags_gin
ON ${schema}.events USING gin (tags);
ANALYZE ${schema}.events;
`);
const after = planReport(
await client.query(`EXPLAIN (ANALYZE, BUFFERS, FORMAT JSON) ${query}`),
);
emit(
'planner',
'after-index',
`После B-tree: ${planLine(after)}; execution=${after.executionMs.toFixed(2)} ms`,
);
const sizes = await client.query(
`
SELECT c.relname, pg_relation_size(c.oid)::bigint AS bytes
FROM pg_class AS c
JOIN pg_namespace AS n ON n.oid = c.relnamespace
WHERE n.nspname = $1 AND c.relkind = 'i'
ORDER BY bytes DESC
`,
[schema],
);
emit(
'indexes',
'size',
`Размеры индексов: ${sizes.rows
.map((row) => `${row.relname}=${Math.round(Number(row.bytes) / 1024)} KiB`)
.join(', ')}`,
);
emit(
'optimizer',
'decision',
'Индекс не является приказом: planner выбирает Seq Scan, Index Scan или Bitmap Scan по статистике, селективности и стоимости',
);
} finally {
client.release();
}
});
}
export async function databaseTransactionsAndLocks(emit) {
await withDatabaseLab(emit, async ({ pool, schema }) => {
await pool.query(`
CREATE TABLE ${schema}.accounts (
id integer PRIMARY KEY,
balance integer NOT NULL CHECK (balance >= 0),
version integer NOT NULL DEFAULT 0
);
INSERT INTO ${schema}.accounts (id, balance) VALUES (1, 1000);
`);
const first = await pool.connect();
const second = await pool.connect();
try {
await Promise.all([configureClient(first), configureClient(second)]);
await first.query('BEGIN ISOLATION LEVEL READ COMMITTED');
const rcBefore = await first.query(
`SELECT balance FROM ${schema}.accounts WHERE id = 1`,
);
await second.query(
`UPDATE ${schema}.accounts SET balance = 1100 WHERE id = 1`,
);
const rcAfter = await first.query(
`SELECT balance FROM ${schema}.accounts WHERE id = 1`,
);
await first.query('ROLLBACK');
emit(
'isolation',
'read-committed',
`READ COMMITTED: первый SELECT=${rcBefore.rows[0].balance}, второй SELECT=${rcAfter.rows[0].balance}`,
);
await pool.query(
`UPDATE ${schema}.accounts SET balance = 1000, version = 0 WHERE id = 1`,
);
await first.query('BEGIN ISOLATION LEVEL REPEATABLE READ');
const rrBefore = await first.query(
`SELECT balance FROM ${schema}.accounts WHERE id = 1`,
);
await second.query(
`UPDATE ${schema}.accounts SET balance = 1100 WHERE id = 1`,
);
const rrAfter = await first.query(
`SELECT balance FROM ${schema}.accounts WHERE id = 1`,
);
await first.query('ROLLBACK');
emit(
'isolation',
'repeatable-read',
`REPEATABLE READ: первый SELECT=${rrBefore.rows[0].balance}, второй SELECT=${rrAfter.rows[0].balance}`,
);
await pool.query(
`UPDATE ${schema}.accounts SET balance = 1000, version = 0 WHERE id = 1`,
);
await first.query('BEGIN');
await first.query(
`SELECT balance FROM ${schema}.accounts WHERE id = 1 FOR UPDATE`,
);
await second.query('BEGIN');
let secondAcquired = false;
const waitStarted = performance.now();
const secondLock = second
.query(
`SELECT balance FROM ${schema}.accounts WHERE id = 1 FOR UPDATE`,
)
.then((result) => {
secondAcquired = true;
return result;
});
await new Promise((resolve) => setTimeout(resolve, 120));
emit(
'lock',
'wait',
`SELECT FOR UPDATE: вторая транзакция ждёт блокировку=${!secondAcquired}`,
);
await first.query(
`UPDATE ${schema}.accounts SET balance = balance - 100 WHERE id = 1`,
);
await first.query('COMMIT');
await secondLock;
const waitedMs = performance.now() - waitStarted;
await second.query(
`UPDATE ${schema}.accounts SET balance = balance - 200 WHERE id = 1`,
);
await second.query('COMMIT');
const pessimistic = await pool.query(
`SELECT balance FROM ${schema}.accounts WHERE id = 1`,
);
emit(
'lock',
'pessimistic',
`Пессимистичная блокировка ждала ${waitedMs.toFixed(0)} ms; итоговый balance=${pessimistic.rows[0].balance}`,
);
await pool.query(
`UPDATE ${schema}.accounts SET balance = 1000, version = 0 WHERE id = 1`,
);
const snapshotA = await first.query(
`SELECT balance, version FROM ${schema}.accounts WHERE id = 1`,
);
const snapshotB = await second.query(
`SELECT balance, version FROM ${schema}.accounts WHERE id = 1`,
);
const updateA = await first.query(
`UPDATE ${schema}.accounts
SET balance = $1, version = version + 1
WHERE id = 1 AND version = $2`,
[snapshotA.rows[0].balance - 100, snapshotA.rows[0].version],
);
const updateB = await second.query(
`UPDATE ${schema}.accounts
SET balance = $1, version = version + 1
WHERE id = 1 AND version = $2`,
[snapshotB.rows[0].balance - 200, snapshotB.rows[0].version],
);
emit(
'lock',
'optimistic',
`Оптимистичная версия: update A=${updateA.rowCount}, stale update B=${updateB.rowCount}; 0 означает конфликт`,
);
} finally {
await Promise.all([rollbackQuietly(first), rollbackQuietly(second)]);
first.release();
second.release();
}
});
}
export async function databaseJoinsAndMaterializedViews(emit) {
await withDatabaseLab(emit, async ({ pool, schema }) => {
const client = await pool.connect();
try {
await configureClient(client);
emit(
'dataset',
'seed',
'Создаём 2 000 клиентов и 30 000 заказов для JOIN и агрегирования',
);
await client.query(`
CREATE TABLE ${schema}.customers (
id integer PRIMARY KEY,
name text NOT NULL,
active boolean NOT NULL
);
CREATE TABLE ${schema}.orders (
id bigint GENERATED ALWAYS AS IDENTITY PRIMARY KEY,
customer_id integer NOT NULL REFERENCES ${schema}.customers(id),
amount numeric(12, 2) NOT NULL,
created_at timestamptz NOT NULL DEFAULT now()
);
INSERT INTO ${schema}.customers (id, name, active)
SELECT g, 'customer-' || g, g % 5 <> 0
FROM generate_series(1, 2000) AS g;
INSERT INTO ${schema}.orders (customer_id, amount, created_at)
SELECT
(g % 2000) + 1,
((g % 5000) + 100)::numeric / 10,
now() - (g * interval '1 minute')
FROM generate_series(1, 30000) AS g;
CREATE INDEX orders_customer_id_idx
ON ${schema}.orders (customer_id);
ANALYZE ${schema}.customers;
ANALYZE ${schema}.orders;
`);
const joinPlan = planReport(
await client.query(`
EXPLAIN (ANALYZE, BUFFERS, FORMAT JSON)
SELECT c.id, c.name, sum(o.amount) AS total
FROM ${schema}.customers AS c
JOIN ${schema}.orders AS o ON o.customer_id = c.id
WHERE c.active
GROUP BY c.id, c.name
ORDER BY total DESC
LIMIT 20
`),
);
emit(
'join',
'plan',
`JOIN plan: ${planLine(joinPlan)}; execution=${joinPlan.executionMs.toFixed(2)} ms`,
);
const sampleCustomers = await client.query(
`SELECT id FROM ${schema}.customers ORDER BY id LIMIT 20`,
);
const nPlusOneStarted = performance.now();
for (const customer of sampleCustomers.rows) {
await client.query(
`SELECT count(*) FROM ${schema}.orders WHERE customer_id = $1`,
[customer.id],
);
}
const nPlusOneMs = performance.now() - nPlusOneStarted;
const oneQueryStarted = performance.now();
await client.query(`
SELECT c.id, count(o.id)
FROM ${schema}.customers AS c
LEFT JOIN ${schema}.orders AS o ON o.customer_id = c.id
WHERE c.id <= 20
GROUP BY c.id
`);
const oneQueryMs = performance.now() - oneQueryStarted;
emit(
'query-shape',
'n-plus-one',
`N+1: 21 round trips=${nPlusOneMs.toFixed(2)} ms; один JOIN=1 round trip=${oneQueryMs.toFixed(2)} ms`,
);
await client.query(`
CREATE MATERIALIZED VIEW ${schema}.customer_totals AS
SELECT customer_id, count(*)::int AS orders_count, sum(amount) AS total
FROM ${schema}.orders
GROUP BY customer_id;
CREATE UNIQUE INDEX customer_totals_customer_id_idx
ON ${schema}.customer_totals (customer_id);
`);
const before = await client.query(
`SELECT total FROM ${schema}.customer_totals WHERE customer_id = $1`,
[42],
);
await client.query(
`INSERT INTO ${schema}.orders (customer_id, amount) VALUES ($1, $2)`,
[42, 999],
);
const stale = await client.query(
`SELECT total FROM ${schema}.customer_totals WHERE customer_id = $1`,
[42],
);
await client.query(`REFRESH MATERIALIZED VIEW ${schema}.customer_totals`);
const refreshed = await client.query(
`SELECT total FROM ${schema}.customer_totals WHERE customer_id = $1`,
[42],
);
emit(
'materialized-view',
'refresh',
`Materialized View: было=${before.rows[0].total}, до REFRESH=${stale.rows[0].total}, после=${refreshed.rows[0].total}`,
);
emit(
'sql',
'control',
'Raw SQL здесь параметризован и видим; ORM полезен, пока команда проверяет сгенерированный SQL, планы, N+1 и границы транзакций',
);
} finally {
client.release();
}
});
}
The emit(...) calls become live-trace rows. await and Promise keep the HTTP stream open until the scenario completes.
Practical patterns worth keeping nearby
Compare the goal, code, and caveats instead of memorizing syntax without a model.
Constraint instead of convention
Prevent a negative balance for every database client.
CREATE TABLE accounts (
id bigint GENERATED ALWAYS AS IDENTITY PRIMARY KEY,
balance numeric(14, 2) NOT NULL CHECK (balance >= 0)
);- A controller check does not protect writes from a worker or manual SQL.
- A cross-row invariant may require a transaction.
Parameterized SQL
Pass user input without SQL injection.
const result = await pool.query(
'SELECT id, email FROM users WHERE email = $1',
[email],
);- Table names and sort directions are identifiers, not values; choose them from an allowlist.
One client per transaction
Create an order and ledger entry atomically.
const client = await pool.connect();
try {
await client.query('BEGIN');
const order = await client.query(insertOrderSql, values);
await client.query(insertLedgerSql, [order.rows[0].id]);
await client.query('COMMIT');
} catch (error) {
await client.query('ROLLBACK');
throw error;
} finally {
client.release();
}- Two independent pool.query calls cannot replace this client.
Constraint as a domain result
Handle a race on a unique email correctly.
try {
await users.insert(email);
} catch (error) {
if (error.code === '23505') {
throw new EmailAlreadyExistsError(email);
}
throw error;
}- A preliminary SELECT does not replace UNIQUE; a race exists before INSERT.
Common misconceptions
The myth is on the left; the accurate model is on the right.
DTO validation is sufficient for integrity.
A DTO protects one input. A constraint protects the data from all inputs and concurrent writes.
ACID automatically preserves every business rule.
The database preserves expressed constraints and correctly implemented transactions.
Manual string escaping is a safe query API.
Use driver parameters for values and an allowlist for dynamic identifiers.
BEGIN through pool.query covers later pool.query calls.
A pool can choose another connection; a transaction belongs to one physical connection.
Explain it in your own words
If you can explain the answer without quoting documentation, your mental model is starting to take shape.
- Which invariants from your last project belong in the database?
- Why does SELECT before INSERT not guarantee uniqueness?
- How does atomicity differ from consistency?
- Why is SQLSTATE safer than error text?
- What risks accompany a NOT NULL migration on a large table?