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database

أفضل ذكاء اصطناعي لـ Generate a SQL query

Generate SQL queries from plain English — SELECTs, JOINs, GROUP BYs, CTEs, window functions, or specialized queries for PostgreSQL, MySQL, BigQuery, etc.

آخر تحديث May 5, 2026sqldatabasequerypostgresqlmysqldata
أفضل ذكاء اصطناعي لهذه المهمة

Claude

Claude produces clean, well-structured SQL with clear reasoning about query optimization, NULL handling, and the trade-offs between alternative formulations. It's the most reliable general-purpose option across PostgreSQL, MySQL, BigQuery, and Snowflake — and explains each clause well enough that you can modify the query yourself afterward instead of treating it as a black box.

افتح Claude
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SQL for Data Science

UC Davis · Coursera · 14 hours · Beginner

Covers query fundamentals from SELECT through JOINs, subqueries, window functions. Lets you read AI-generated SQL critically — spot the unnecessarily complex queries, the inefficient joins, and the cases where the AI invented a column.

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قالب التوجيه
Generate a SQL query.

Database: [PostgreSQL / MySQL / BigQuery / Snowflake / SQL Server]

Schema:
- Table 1: [table_name]
  Columns: [list with types]
- Table 2: [table_name]
  Columns: [list with types]
- Relationships: [foreign keys]

What I want:
[PLAIN ENGLISH DESCRIPTION OF THE RESULT]

Constraints:
- Time period: [if relevant]
- Filters: [if relevant]
- Sort by: [if relevant]

Please:
1. Write the query
2. Explain in 2 sentences what each part does
3. Flag any indexes that should exist for this query to run fast
4. Suggest one alternative version if there's a meaningfully different approach
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شاهد الفرق

قبل وبعد استخدام هذا التوجيه

قبل — بدون التوجيه

SELECT COUNT(*) FROM users JOIN orders ON users.id = orders.user_id WHERE orders.created_at > '2025-01-01'; This counts the number of orders made by users since 2025.

بعد — مع التوجيه

Better query depending on which question you actually want answered: If you want "number of orders since 2025": SELECT COUNT(*) FROM orders WHERE created_at >= '2025-01-01'::date; The original JOIN to users is unnecessary — orders already has user_id, you're not filtering by any user attribute. If you want "number of distinct users who placed at least one order since 2025": SELECT COUNT(DISTINCT user_id) FROM orders WHERE created_at >= '2025-01-01'::date; This is what you probably meant if you JOIN'd to users in the first place. Three issues with the original: 1. `> '2025-01-01'` excludes orders made on Jan 1, 2025 at exactly 00:00:00. Use `>=`. 2. The JOIN inflates the count if a user can appear multiple times in users (shouldn't happen with a unique users.id, but if id isn't unique you'll over-count). Verify with: `SELECT id, COUNT(*) FROM users GROUP BY id HAVING COUNT(*) > 1;` 3. String comparison vs date — `'2025-01-01'` works in PostgreSQL because of implicit casting, but it's safer to cast explicitly so behavior is predictable across dialects. Indexes that should exist: `orders(created_at)` for the WHERE clause to be fast on this column. If you don't have it, EXPLAIN ANALYZE will show a Seq Scan. Sanity check: `SELECT MIN(created_at), MAX(created_at) FROM orders;` to confirm your date filter range is in the data at all.

الخيار البديل

AI2SQL

Better when you have a production database and need queries that respect a real schema. Connects directly to your tables across 10+ SQL dialects so it never hallucinates column names — worth the setup for ongoing analyst work, overkill for one-off queries.

افتح AI2SQL

الأسئلة الشائعة

  • Why does my AI-generated query return wrong results?

    Almost always one of three issues — (1) wrong assumption about column types (string vs date), (2) NULL handling (== NULL doesn't work, use IS NULL), or (3) implicit type casting in JOINs. Paste a sample row and the error message back to the AI; it usually fixes on the second try.

  • Can AI optimize slow SQL queries?

    Yes, with caveats. Claude and ChatGPT can spot common issues (missing indexes, N+1 patterns, unnecessary subqueries) but can't see your actual query plan. For real optimization, paste the EXPLAIN ANALYZE output along with the query.

  • Should I let AI tools connect directly to my production database?

    Only with read-only credentials and never for write operations. AI agents that "execute SQL on your behalf" are fine for staging/sandbox environments. For production, always review the query before running, especially anything that includes UPDATE, DELETE, or DDL.

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