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Overview

Baileys does not include built-in persistent storage for messages, chats, or contacts. You must implement your own data store to persist WhatsApp data across sessions.
Storing an entire chat history in memory is inefficient and not recommended for production applications. Implement database-backed storage for real-world use cases.

Why You Need a Store

A message store is essential for:
  • Message retries - Retrying failed message sends
  • Poll vote decryption - Decrypting poll vote updates
  • Message history - Accessing previous messages
  • Chat context - Maintaining conversation state
  • Quote messages - Retrieving quoted messages

In-Memory Store (Custom Implementation)

As of Baileys v7.0.0, the built-in makeInMemoryStore function has been removed. You must implement your own data store.
While earlier versions of Baileys included a reference implementation, v7.0.0+ requires you to build a custom store tailored to your needs. This gives you more control and allows you to use databases that fit your scale requirements.

Basic In-Memory Store Example

Here’s a simple in-memory implementation for reference:
Your custom store should provide:
  • Chat storage - Store chat metadata and state
  • Message storage - Indexed by JID for quick retrieval
  • Contact storage - User and group contact information
  • Persistence - Save to disk/database periodically
  • Query methods - Load messages by JID, pagination support

Implementing getMessage for Retries

The socket config accepts a getMessage function for message retries and poll updates:

getMessage Implementation

From Example/example.ts:226:

Using getMessage for Poll Votes

From Example/example.ts:167:

Database Store Implementation

MongoDB Example

PostgreSQL Example

Storing Events

Messages

Message Updates

Chats

Contacts

Message Retrieval Helpers

Get Last Message in Chat

Load Message History

Best Practices

Store Implementation Tips:
  1. Index efficiently - Index by remoteJid, id, and fromMe for fast lookups
  2. Serialize properly - Use BufferJSON for Buffer/Uint8Array fields
  3. Handle updates - Use upsert operations for idempotency
  4. Batch operations - Batch database writes for performance
  5. Clean old data - Implement retention policies for old messages
  6. Backup regularly - Regular backups prevent data loss
  7. Handle errors - Gracefully handle database errors

Performance Optimization

Batch Writes

Caching

Data Retention

See Also