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How to Optimize SQLite for Production in 2026

18 minADVANCED
OptimisationBase de donnéesSQLite
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Introduction

SQLite is often underestimated for production environments. However, with the right configurations and advanced techniques, it can handle millions of records with latency under 1 ms. This tutorial guides you through real optimization: enabling WAL mode, creating smart composite indexes, using FTS5 for full-text search, and precise PRAGMA tuning. Each section includes directly usable code.

Prerequisites

  • SQLite 3.42+
  • Solid knowledge of SQL and indexing
  • Node.js 20+ with better-sqlite3
  • Access to a terminal and code editor

Enable WAL Mode

optimize.sql
PRAGMA journal_mode = WAL;
PRAGMA synchronous = NORMAL;
PRAGMA wal_autocheckpoint = 1000;

WAL mode enables concurrent reads without locking. synchronous=NORMAL offers the best performance/security compromise. Automatic checkpointing prevents the WAL file from growing indefinitely.

Create Composite Indexes

indexes.sql
CREATE INDEX idx_orders_customer_date 
ON orders(customer_id, created_at DESC) 
WHERE status = 'completed';

A composite index covering the most filtered and sorted columns avoids full scans. The partial WHERE clause reduces index size and improves performance for common queries.

Configure Critical PRAGMA

pragma.sql
PRAGMA cache_size = -64000;
PRAGMA temp_store = MEMORY;
PRAGMA mmap_size = 30000000000;

A 64 MB cache in negative notation, temporary storage in memory, and 30 GB mmap allow SQLite to fully utilize available RAM without disk overhead.

Implement FTS5

fts5.sql
CREATE VIRTUAL TABLE documents_fts 
USING fts5(title, content, tokenize='porter unicode61');

FTS5 with porter and unicode61 tokenizer provides performant and relevant full-text search. It automatically handles word inflection and special characters.

Optimized Query with FTS5

search.sql
SELECT d.id, d.title, rank 
FROM documents d
JOIN documents_fts ON d.id = documents_fts.rowid
WHERE documents_fts MATCH 'optimisation production'
ORDER BY rank;

Joining with documents_fts and using rank enables relevance-based sorting. SQLite uses the FTS5 index to avoid any table scans.

Best Practices

  • Always enable WAL and verify regular checkpointing
  • Create partial indexes only on active data
  • Use explicit transactions for batch operations
  • Monitor WAL and journal file sizes
  • Run VACUUM after large deletions

Common Mistakes to Avoid

  • Forgetting to switch to WAL before loading data
  • Creating too many indexes without testing real queries
  • Ignoring cache_size and mmap_size PRAGMA settings
  • Not setting size limits for WAL files

Going Further

Deepen these concepts with our expert training on embedded databases. Discover our Learni training.