Pino vs Winston in 2026: Node.js Logging Guide

TL;DR

Pino for production performance; Winston for flexible multi-destination logging. Pino (~9M weekly downloads) uses async logging to stdout — it's 5-8x faster than Winston and is the default for Fastify. Winston (~15M downloads) is more configurable — multiple transports, custom formats, rich ecosystem. For high-throughput Node.js services, Pino's performance advantage is real. For complex logging pipelines, Winston's flexibility wins.

Key Takeaways

• Winston: ~15M weekly downloads — Pino: ~9M (npm, March 2026)
• Pino is 5-8x faster — minimal serialization, async writes
• Winston has more transports — file, HTTP, MongoDB, Cloudwatch, etc.
• Pino is Fastify's default — built by the same team
• Both output JSON — structured logging is the standard for production

---

Performance

The performance gap between Pino and Winston is not a minor optimization — it's architectural. Winston's design processes log entries synchronously: format the message, apply transforms, write to each transport. Each transport write is typically synchronous file I/O or synchronous network I/O (for HTTP transports). When your application logs frequently, this synchronous I/O directly competes with request handling on the Node.js event loop.

Pino's approach is different: write a minimal JSON string to stdout asynchronously and return immediately. The actual I/O (writing to a file, sending to a log aggregator, forwarding to CloudWatch) is handled by a separate process outside Node.js. This "log to stdout and let the infrastructure handle routing" philosophy keeps logging completely off the main event loop. For a service handling 10,000 requests per second with one log line per request, the difference between 2ms per log call (Winston) and 0.004ms per log call (Pino) is 20 seconds of CPU per second of traffic — a real bottleneck.

Benchmark: 100,000 log messages

Logger      | Time    | Ops/sec
------------|---------|----------
Pino        | 450ms   | 222,000
Bunyan      | 1,100ms |  91,000
Winston     | 2,800ms |  36,000
Morgan      | 3,400ms |  29,000

Why Pino is faster:
- Writes to stdout asynchronously (defers I/O)
- JSON serialization optimized for speed
- Minimal in-process work — log collection happens outside Node.js
- No synchronous file writes

---

Basic Usage

Pino's API is deliberately minimal. You create a logger, configure the level and any serializers, and call logger.info(), logger.error(), etc. The structured data (the object you pass as the first argument) is merged into the JSON output. This is more ergonomic than Winston's approach of passing data as a separate object after the message, and it produces more consistent output because the data fields are always in the same position.

Winston's createLogger function is more verbose but more powerful. The format.combine() chain lets you define exactly how log entries are serialized — adding timestamps, error stack traces, JSON formatting, or custom transforms. The transports array defines where logs go simultaneously. This flexibility is Winston's core value proposition.

// Pino — structured JSON logging
import pino from 'pino';

const logger = pino({
  level: process.env.LOG_LEVEL ?? 'info',
  // Development: use pino-pretty for human-readable output
  // Production: raw JSON goes to stdout → collected by log aggregator
});

logger.info('Server started');
logger.info({ port: 3000, env: 'production' }, 'Server listening');
logger.warn({ userId: '123', action: 'login' }, 'Failed login attempt');
logger.error({ err, requestId }, 'Unhandled error in request handler');

// Child logger — adds context to all log lines
const reqLogger = logger.child({ requestId: req.id });
reqLogger.info('Processing request');
reqLogger.info({ userId }, 'User authenticated');
// All lines include requestId automatically

// Winston — flexible transports
import winston from 'winston';

const logger = winston.createLogger({
  level: 'info',
  format: winston.format.combine(
    winston.format.timestamp(),
    winston.format.errors({ stack: true }),
    winston.format.json()
  ),
  transports: [
    // Production: structured JSON to stdout
    new winston.transports.Console(),
    // Error file
    new winston.transports.File({ filename: 'error.log', level: 'error' }),
    // All logs
    new winston.transports.File({ filename: 'combined.log' }),
  ],
});

// Development-only: pretty print
if (process.env.NODE_ENV !== 'production') {
  logger.add(new winston.transports.Console({
    format: winston.format.prettyPrint(),
  }));
}

---

Express Integration

// Pino — with pino-http
import pino from 'pino';
import pinoHttp from 'pino-http';

const logger = pino();
const httpLogger = pinoHttp({ logger });

app.use(httpLogger);
// Automatically logs all requests with timing, status code, etc.

// In route handlers, use req.log (child logger with requestId):
app.get('/users/:id', (req, res) => {
  req.log.info({ userId: req.params.id }, 'Fetching user');
  // ...
});

// Winston with Morgan
import winston from 'winston';
import morgan from 'morgan';

const morganStream = {
  write: (message) => logger.http(message.trim()),
};

app.use(morgan('combined', { stream: morganStream }));

---

Log Levels

// Pino levels (numeric, faster comparison)
// fatal: 60, error: 50, warn: 40, info: 30, debug: 20, trace: 10
logger.fatal('Critical failure');
logger.error({ err }, 'Database connection failed');
logger.warn('Deprecated API usage');
logger.info('Request processed');
logger.debug({ query }, 'SQL query executed');
logger.trace('Verbose debugging');

// Winston levels (customizable)
// Default: error, warn, info, http, verbose, debug, silly
logger.error('Database connection failed');
logger.warn('Rate limit approaching');
logger.info('User registered');
logger.http('GET /api/users 200 45ms'); // HTTP-specific level
logger.debug('Query parameters:', params);

---

Package Health

Both packages are actively maintained but on different trajectories. Pino's growth from ~3M to ~9M weekly downloads between 2022 and 2026 reflects the broader adoption of Fastify and performance-conscious Node.js development. Winston's 15M downloads include a large legacy installed base — many applications have been running Winston for years and have no strong reason to migrate.

Package	Weekly Downloads	Last Release	GitHub Stars	Backing
winston	~15M	Active (2026)	22K+	Community
pino	~9M	Active (2026)	13K+	Nearform/Community
pino-http	~3M	Active (2026)	1.5K+	Same team
pino-pretty	~5M	Active (2026)	1.5K+	Same team

Winston's high download count alongside a community-only maintenance model is a mild concern for long-term stability. There's no commercial entity sponsoring Winston's development. Pino benefits from Nearform's involvement and the Fastify team's vested interest in keeping it performant.

---

TypeScript Support

Both libraries have TypeScript definitions, but their TypeScript experiences differ. Pino ships TypeScript definitions in the main package, and the types are generally well-maintained. The core pino.Logger type is generic, allowing you to type the bindings (the properties added by logger.child(bindings)):

import pino from 'pino';

// Typed base logger with custom bindings
const logger = pino({
  level: 'info',
});

// Type the child logger's bindings
interface RequestBindings {
  requestId: string;
  userId?: string;
  traceId?: string;
}

// Child logger with typed bindings
const reqLogger: pino.Logger<never> = logger.child<RequestBindings>({
  requestId: crypto.randomUUID(),
});

// Custom log level type extension
type CustomLevel = 'audit';
const auditLogger = pino<CustomLevel>({
  customLevels: { audit: 35 },
  useOnlyCustomLevels: false,
});
auditLogger.audit({ userId, action }, 'User action logged');

Winston's TypeScript support has historically been more problematic, but winston@3.x ships with adequate types. The format pipeline types are complex because Winston's format is designed to be composable:

import winston, { Logger, format } from 'winston';
import type { TransformableInfo } from 'logform';

// Custom format with TypeScript
const addRequestContext = format((info: TransformableInfo) => {
  const context = AsyncLocalStorage.getStore() as RequestContext | undefined;
  if (context) {
    info.requestId = context.requestId;
    info.userId = context.userId;
  }
  return info;
});

const logger: Logger = winston.createLogger({
  level: 'info',
  format: format.combine(
    addRequestContext(),
    format.timestamp(),
    format.errors({ stack: true }),
    format.json(),
  ),
  transports: [new winston.transports.Console()],
});

---

Pino in Production

Production Pino setup involves several packages beyond the core library. The ecosystem is coherent — all maintained by the Pino team or close contributors.

pino-pretty transforms Pino's JSON output into human-readable colored output for development. Critically, pino-pretty is a separate process — you pipe Pino's stdout through it rather than importing it into your application. This means zero performance overhead from pretty-printing in production (you simply don't run it) and clean JSON in production logs.

# Development: pipe through pino-pretty
node server.js | pino-pretty

# Or in package.json:
{
  "scripts": {
    "dev": "node server.js | pino-pretty",
    "start": "node server.js"
  }
}

Redacting sensitive fields prevents accidental PII logging. Pino's redact option uses object path notation:

const logger = pino({
  redact: {
    paths: [
      'password',
      'token',
      '*.authorization',
      'req.headers.cookie',
      'user.creditCard.number',
    ],
    censor: '[REDACTED]',
    remove: false, // Set true to remove field entirely instead of replacing
  },
});

Error serialization in Pino requires the err key specifically. Pino ships a default error serializer that extracts message, stack, and type from Error objects:

logger.error({ err: new Error('Database timeout') }, 'Query failed');
// Output includes: "err":{"type":"Error","message":"Database timeout","stack":"Error: Database..."}

// Custom error serializer for additional properties:
const logger = pino({
  serializers: {
    err: (err) => ({
      type: err.constructor.name,
      message: err.message,
      stack: err.stack,
      code: err.code,        // Custom error code
      statusCode: err.statusCode, // HTTP status if applicable
    }),
  },
});

pino-roll provides log rotation when you do write to files (useful for non-Kubernetes deployments):

import pino from 'pino';
import { createStream } from 'pino-roll';

const logger = pino(
  { level: 'info' },
  await createStream({
    file: './logs/app.log',
    frequency: 'daily',      // Rotate daily
    size: '100m',            // Or rotate when file reaches 100MB
    limit: { count: 7 },     // Keep last 7 log files
  })
);

---

Migrating from Winston to Pino

The migration from Winston to Pino is straightforward in concept but requires touching every logging callsite. The API differences are minor but consistent:

// Winston pattern:
logger.info('Message', { key: 'value' }); // message first, then object
logger.error('Failed', { error: err });

// Pino pattern:
logger.info({ key: 'value' }, 'Message'); // object first, then message
logger.error({ err }, 'Failed'); // err is the conventional key for errors

The most impactful API difference is the argument order. Pino puts the data object first and the message second. This enables Pino's JSON serialization to be faster (it builds the JSON object incrementally, starting with known fields) and produces more consistent output.

Recreating Winston transports in Pino — Winston's file transports are replaced by Pino's stdout + external log rotation approach. Winston's HTTP transport for sending logs to an API becomes a Pino transport:

// Winston HTTP transport → Pino equivalent
// Option 1: Use pino-loki for Loki/Grafana
import pino from 'pino';
import { createWriteStream } from 'pino-loki';

const transport = createWriteStream({
  batching: true,
  interval: 5, // seconds
  host: 'http://loki:3100',
  labels: { service: 'my-api' },
});

const logger = pino({ level: 'info' }, transport);

// Option 2: Custom transport using pino's transport API
const transport = pino.transport({
  target: 'pino-datadog-transport',
  options: {
    apiKey: process.env.DD_API_KEY,
    service: 'my-api',
  },
});

The single most important migration step is switching from synchronous to asynchronous logging patterns. If your Winston setup writes to files directly, Pino's equivalent is the async transport pattern above. Don't recreate synchronous file writes in Pino — that defeats the performance advantage entirely.

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When to Choose

Choose Pino when:

• High-throughput Node.js service (Fastify, Express with many req/sec)
• JSON logging to stdout → log aggregator (production standard)
• Minimal logging overhead is required
• Using Fastify (Pino is built in)

Choose Winston when:

• Multiple log destinations (file + database + external service)
• Complex log formatting or transformation pipelines
• Legacy codebase already using Winston
• You need many community transport plugins (Cloudwatch, Datadog, etc.)
• File-based logging is a requirement

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Compare Pino and Winston package health on PkgPulse. For a full ecosystem view, see best Node.js logging libraries 2026. Browse all packages in the PkgPulse directory.