Oracle to SQL Server Converter - Free Online Tool 2025

Moving from Oracle to SQL Server is a significant migration project for many enterprises, driven by cost control, cloud strategy, or platform standardization goals. The process is complex: incompatible data types, major syntax differences, and procedural language gaps can slow down projects and introduce risk. Manual conversion requires deep expertise in both platforms and often results in subtle errors, inconsistent results, and long testing cycles. AI2sql solves these challenges by translating plain English requirements into accurate, production-ready SQL Server syntax—eliminating human error and dramatically accelerating your migration roadmap.

Oracle to SQL Server Migration Overview

Oracle and SQL Server are both enterprise-grade relational database systems, but their SQL implementations differ in critical ways. Understanding these differences is vital to a successful migration:

• Data types and constraints often lack 1:1 mapping.

• PL/SQL vs T-SQL: Procedural logic and function definitions differ significantly.

• Indexing, sequence, and trigger mechanisms use different standards.

AI2sql empowers organizations by removing syntax barriers and ensuring correct, optimized SQL output for the target system.

Key Syntax Differences: Oracle vs SQL Server

Data Type Mapping Guide

Accurate data type mapping is critical to avoid data loss or corruption. Here are common conversions:

Common Conversion Challenges

• Function and keyword differences (Oracle’s NVL() vs SQL Server’s ISNULL())

• Hierarchical queries: CONNECT BY vs WITH RECURSIVE

• PL/SQL to T-SQL stored procedure translation

• Role, user, and privilege syntax

• Constraint naming and validation behaviors

Manual conversion is prone to time-consuming errors. The AI2sql platform dramatically shortens conversion time, reduces risk, and provides confidence in your migration accuracy.

Step-by-Step Migration Process

1. Assess dependencies: Inventory Oracle objects—tables, views, procedures, triggers.

2. Map schema: Convert DDL (tables, sequences, constraints) using a schema conversion guide.

3. Translate SQL logic: Rewrite queries, joins, and procedural code for SQL Server.

4. Data migration: Extract-transform-load data, handling data type mismatches.

5. Test and validate: Run integration tests to verify behavior.

6. Optimize: Tune for SQL Server performance, indexing, and concurrency.

Performance Considerations

• SQL Server query plans and optimizers differ from Oracle’s—review indexing strategies and statistics updates.

• Batch and bulk loading methods may need adjustment (BULK INSERT for SQL Server).

• SQL Server’s transaction isolation and locking model may affect migration outcomes.

Schema Migration Best Practices

• Normalize object names to meet SQL Server standards (avoid reserved keywords, apply proper case sensitivity).

• Use scripts to automate constraint and index recreation.

• Convert triggers and sequences to SQL Server-compatible logic, using computed columns and IDENTITY as needed.

Testing and Validation

• Set up parallel test environments.

• Validate row counts, referential integrity, and procedural logic results.

• Use SQL Server Profiler or Extended Events to identify performance regressions.

Rollback Strategies

• Maintain backup snapshots of the Oracle database pre-migration.

• Script reverse ETL to revert critical tables if needed.

• Document all DDL and transformation steps for auditability.

Troubleshooting Common Conversion Errors

• Data truncation: Caused by smaller target varchar/numeric types; check mapping tables.

• NULL handling differences: Confirm default values and NOT NULL constraints.

• Function translation issues: Replace Oracle-specific functions (e.g., NVL()) with SQL Server equivalents.

• Date format mismatches: Standardize to yyyy-mm-dd before migration.

AI2sql: Generate SQL Server Queries from Natural Language

No more learning complex T-SQL syntax or worrying about subtle PL/SQL incompatibilities. Simply enter your data requirements in plain English—like ‘Select the top 5 products by revenue last quarter’—and AI2sql outputs optimized SQL Server queries instantly. Supports all database objects, functions, DDL, and typical migration operations with enterprise-grade accuracy.

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Oracle to SQL Server: Practical Conversion Examples

AI2sql Feature Highlights for Oracle to SQL Server Migration

• Supports 15+ database engines, including Oracle, SQL Server, MySQL, PostgreSQL, and more

• Natural language to syntax—no SQL Server experience required

• Guaranteed error-free syntax and optimized queries

• Used by 50,000+ developers & IT teams worldwide

• Automatic data type mapping and function translation

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SQL Server Performance Tips After Migration

• Rebuild and update indexes for new data distribution.

• Review execution plans for converted queries; refactor where needed.

• Avoid deprecated T-SQL syntax for maintainability.

Conclusion: Streamline Oracle to SQL Server Migration with AI2sql

Transitioning from Oracle to SQL Server doesn't have to be painful or risky. With the right strategy, clear syntax guides, and automated tools like AI2sql, you can deliver reliable, high-performance migrations—on time and without legacy errors. Stop wasting cycles on manual rewriting and focus on business outcomes: let AI2sql translate your requirements into precise SQL Server code, instantly.

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More SQL Server Migration Resources:

• Try AI2sql SQL Server Generator

• SQL Server SQL Tutorial

• Oracle Migration Tools