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JSON to SQL

Convert JSON data to SQL INSERT and CREATE TABLE statements with one click, supporting nine major database dialects including MySQL/PostgreSQL/SQL Server, with local processing ensuring data security

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Tool Description

JSON to SQL is an online JSON to SQL tool offering free daily quotano installation, no registration, ready to use. It transforms .json data files into SQL INSERT and CREATE TABLE statements with one click, supporting nine major database dialects: MySQL, MariaDB, PostgreSQL, SQLite, Oracle, SQL Server, IBM DB2, SAP HANA, and DaMeng DM, with customizable table names and batch insert sizes. All processing runs locally in your browser for 100% privacy. Whether for data migration, database initialization, or data exchange, it delivers results comparable to professional database tools.

How to Use

  1. Upload JSON

    Click the upload area or drag and drop JSON files (.json) into the upload box. The file should contain a JSON array of objects (e.g., [{"id":1,"name":"John"},...]).

  2. Set Parameters

    Select the target database type in the parameter panel, and optionally set table name, batch size, and whether to generate CREATE TABLE statements.

  3. Process & Download

    After conversion, click "Download" to get your SQL file — multiple files support batch download as a ZIP archive.

Use Cases

  • Data Migration: Quickly convert JSON data from APIs or NoSQL database exports into SQL scripts for direct import into MySQL, PostgreSQL, and other relational databases
  • Database Initialization: Convert JSON configuration data and test data into SQL with CREATE TABLE statements for new project database setup or test data preparation
  • Data Analysis & Exchange: Batch convert JSON data from third-party APIs into SQL format for querying, analysis, and data integration in relational databases

Key Advantages

  1. Free Daily Quota

    Free usage every day covers everyday data conversion needs at zero cost; frequent or professional users can unlock more via a membership.

  2. Privacy & Security

    All conversion runs entirely in your browser — files are never uploaded to any server, keeping your data safe.

  3. Smart Type Inference

    Automatically detects numeric, boolean, and date types to generate appropriate column types.

  4. Multi-Dialect Support

    Compatible with MySQL, PostgreSQL, Oracle, SQL Server and five other major database dialects, generating the correct syntax automatically.

  5. Flexible Output

    Customizable table names and batch insert sizes, with optional CREATE TABLE statements.

  6. One-Click Completion

    No manual SQL writing needed — upload JSON to generate complete INSERT and CREATE TABLE statements in one click, saving time and effort.

Database Dialect Differences

Different databases have variations in identifier quoting, data types, and auto-increment syntax. This tool automatically generates the appropriate SQL syntax based on your selected database type:

Database Identifier Quote Special Syntax
MySQL `column_name` AUTO_INCREMENT, ENGINE=InnoDB
MariaDB `column_name` AUTO_INCREMENT, ENGINE=InnoDB
PostgreSQL "column_name" GENERATED AS IDENTITY, BOOLEAN
SQLite "column_name" AUTOINCREMENT, TEXT, REAL
Oracle "column_name" NUMBER, VARCHAR2, SEQUENCE
SQL Server [column_name] IDENTITY(1,1), NVARCHAR
IBM DB2 "column_name" GENERATED ALWAYS AS IDENTITY
SAP HANA "column_name" COLUMN TABLE, GENERATED AS IDENTITY
DaMeng DM "column_name" IDENTITY(1,1), VARCHAR2

Usage Tips

① For large datasets, use batch inserts (50-500 rows per batch) to speed up imports; ② The tool automatically wraps identifiers in quotes when names contain special characters; ③ Preview the SQL output before executing to confirm table names, column names, and types are as expected.

FAQ

What is a JSON to SQL tool?

A JSON to SQL tool converts JSON data into SQL scripts online. It transforms .json files into INSERT and CREATE TABLE statements with one click, supports multiple database dialects, and runs entirely in your browser.

How do I use the JSON to SQL tool?

Upload a JSON file, choose the database type, and click Start. You can set the target table name and batch insert size, then download the SQL file when done.

What JSON format is supported?

JSON arrays of objects and single JSON objects are supported. For example [{"id":1,"name":"John"},{"id":2,"name":"Jane"}]. All object keys become database column names, and values infer the appropriate SQL column types automatically.

Which database dialects are supported?

MySQL, MariaDB, PostgreSQL, SQLite, Oracle, SQL Server, IBM DB2, SAP HANA, and DaMeng DM are supported. The tool generates the appropriate dialect syntax automatically.

Can the generated SQL be executed directly?

Yes. The generated SQL follows standard syntax and is adapted for each database. We recommend previewing the SQL before execution to verify table and column names; column types in CREATE TABLE statements are auto-inferred and may need minor adjustments.

How are data types inferred?

The tool scans all data in each column and infers the appropriate SQL type. Integers map to INT/BIGINT, decimals to DECIMAL, booleans to TINYINT/BOOLEAN, date-formatted strings to VARCHAR, and so on. Review key column definitions after generation.

What is the maximum supported file size?

Everyday files are handled without issue. This tool runs locally in your browser, so capacity depends on your device. For very large files, we recommend uploading in batches for smooth conversion.

Are uploaded files secure? Will they leak?

Files are processed entirely in your browser and never uploaded to any server. All conversion happens on your device, keeping your data safe.

Do I need to register or pay to use it?

Free usage is granted every day, covering everyday needs at zero cost. No registration is required. When you need higher capacity, a membership unlocks more quota.

Does it work on mobile or tablets?

Yes, mobile is supported. This tool uses a responsive design, so it works on phones, tablets, and desktops — generate SQL anytime, anywhere.

What are the benefits of batch inserts?

Batched INSERTs are significantly more efficient than individual ones. Choose batch size based on data volume: single-row inserts for small datasets (easier to debug), and 50-500 rows per batch for large datasets (faster import speed).

What if the generated SQL fails to execute?

Check the table and column names first. Confirm the generated table name follows the selected database's naming rules and column types match expectations; adjust parameters and re-convert, or manually fine-tune the SQL if needed.

Content last updated:2026-08-10

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