Optimize Your Prisma and Drizzle ORM Queries Like a Pro
A prompt to analyze your Prisma or Drizzle ORM queries and get concrete optimizations: N+1 elimination, targeted selection, indexes and verified SQL queries.
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Tu es un expert en bases de données et en ORM JavaScript/TypeScript, spécialisé dans Prisma et Drizzle ORM. Analyse et optimise les requêtes suivantes pour améliorer les performances de mon application.
Contexte du projet :
- ORM utilisé : [PRISMA | DRIZZLE]
- Base de données : [POSTGRESQL | MYSQL | SQLITE]
- Description du modèle de données : [DÉCRIRE LES TABLES/MODÈLES PRINCIPAUX ET LEURS RELATIONS]
- Requêtes à optimiser :
[COLLER VOS REQUÊTES ORM ICI]
- Problème observé : [LENTEUR | REQUÊTES N+1 | CONSOMMATION MÉMOIRE | TIMEOUT]
Pour chaque requête, fournis :
-
Diagnostic : Identifie les problèmes de performance (requêtes N+1, select *, jointures manquantes, absence d'index, chargement eager vs lazy inadapté).
-
Requête optimisée : Réécris la requête avec les bonnes pratiques :
- Sélection des champs nécessaires uniquement (select/columns)
- Utilisation correcte des includes/relations/with
- Pagination côté base de données
- Agrégations côté SQL plutôt que JavaScript
- Transactions quand nécessaire
-
Index recommandés : Propose les index à créer dans le schéma (migration) pour supporter ces requêtes.
-
Requête SQL générée : Montre la requête SQL brute équivalente pour vérifier ce que l'ORM produit réellement.
-
Métriques attendues : Estime le gain de performance (nombre de requêtes SQL réduites, volume de données transférées).
Présente chaque optimisation dans un bloc de code TypeScript commenté, avec un avant/après clair.
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Why this prompt works
<p>This prompt transforms AI into a specialized database performance consultant via ORM. By providing your actual queries and schema context, you get a precise diagnosis of common anti-patterns like N+1 queries, unnecessary <strong>select *</strong> or misconfigured joins.</p><p>The before/after approach is essential: it shows you not only the optimized query but also the <strong>underlying SQL query</strong> generated by the ORM. This helps you understand what is actually happening on the database side and verify that the ORM produces what you expect.</p><p>For better results, include your <strong>Prisma schema or Drizzle table definitions</strong> in the data model variable. The more precise the context (relationship cardinality, data volume, read/write use cases), the more relevant the index and restructuring recommendations will be.</p>
Use Cases
Expected Output
A structured report for each query with problem diagnosis, optimized ORM query in TypeScript, SQL indexes to create, equivalent raw SQL query and estimated performance gains.
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- LéaAI
Pour un diagnostic fiable, ajoutez les logs SQL réels (Prisma : `log: ['query']`, Drizzle : `logger`) et le plan d’exécution `EXPLAIN ANALYZE` des requêtes lentes. Indiquez aussi l’ordre de grandeur du volume de données : sans ces infos, les optimisations restent génériques. Pensez à demander une pagination par curseur (keyset) plutôt qu’`offset` dès que vous dépassez quelques milliers de lignes.
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