SyBase Database Migration to SQL Server

 Sybase ASC vs. Sybase Database – What’s the Difference?

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1. Sybase Database (General Term)

"Sybase database" is a generic term that refers to any database system developed by Sybase, Inc. Over the years, Sybase has created several database products, including:

• Sybase ASE (Adaptive Server Enterprise) – the most well-known, high-performance relational database.

• Sybase ASA (Adaptive Server Anywhere) – designed for mobile and embedded systems (later became SQL Anywhere).

• Sybase IQ – a column-based database for analytics and reporting.

• Sybase Replication Server, etc.

So, when someone says "Sybase database", they could be referring to any of these products.

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2. Sybase ASC (Adaptive Server Cluster Edition)

Sybase ASC is a specific edition of Sybase ASE (Adaptive Server Enterprise) designed to support database clustering.

• It allows multiple ASE instances to work together as a single clustered database system.

• Designed for high availability and scalability in enterprise environments.

• Useful for handling large workloads and failover between database nodes.

Migrating from SAP ASE (Sybase) to SQL Server

A Comprehensive Step-by-Step Guide with Examples and Best Practices

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Overview

Migrating from SAP ASE (Adaptive Server Enterprise)—formerly known as Sybase—to Microsoft SQL Server can unlock significant advantages: improved performance, better scalability, enhanced integration capabilities, and cost savings. However, it requires careful planning, technical expertise, and attention to detail.

This in-depth guide provides:

• A step-by-step migration framework

• Practical examples and SQL snippets

• Best practices for schema conversion, data migration, and application refactoring

• Strategies for testing and post-migration optimization

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Introduction

Migration is more than data movement—it's a transformation. You’re re-platforming your database architecture, aligning it with modern SQL Server capabilities while preserving business functionality.

This documentation walks you through:

• Pre-migration assessment

• Migration strategies

• Schema and data conversion

• Application and query modifications

• Testing and validation

• Deployment and performance tuning

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Step 1: Assess Your Current SAP ASE Environment

Start with a deep dive into your existing SAP ASE setup.

Key Activities:

• Inventory all database objects (tables, views, triggers, procedures)

• Map dependencies between applications and the database

• Review custom data types, business logic, legacy patterns

• Analyze performance hotspots (e.g., blocking, slow queries)

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Examples:

🔸 List user tables:

        SELECT name FROM sysobjects WHERE type = 'U';

🔸 Check procedure dependencies:

        sp_depends 'usp_CalculateRevenue'

🔸 View top queries by CPU usage:

        SELECT TOP 10 * FROM sysqueryplans ORDER BY cpu_time DESC;

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Step 2: Choose the Right Migration Approach

Your migration strategy should reflect your database’s size, complexity, and mission-criticality.

Method	Use Case	Tools
Manual	Small/simple environments	Scripts, BCP, SSMS
Automated	Medium/large environments	SSMA (SQL Server Migration Assistant)
Hybrid	Complex business logic	SSMA + manual SQL rewriting

Example: Using SSMA

1. Install SSMA for SAP ASE

2. Connect to ASE and SQL Server instances

3. Convert schema → Apply to SQL Server

4. Migrate data via SSMA GUI or scripts

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Step 3: Schema Conversion

SAP ASE and SQL Server differ in:

• Data types

• Procedural syntax

• Built-in functions

Key Tasks:

• Convert ASE types to SQL Server equivalents

• Rewrite stored procedures, triggers, and functions

• Replace unsupported constructs (e.g., text, money)

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Examples:

🔹 Data Type Mapping:

SAP ASE	SQL Server
money	decimal(19,4)
datetime	datetime2
text	varchar(max)

🔹 Stored Procedure:

SAP ASE:

CREATE PROCEDURE sp_get_orders @customer_id INT

AS

BEGIN

    SELECT * FROM orders WHERE customer_id = @customer_id

END

SQL Server:

CREATE PROCEDURE sp_get_orders @customer_id INT

AS

BEGIN

    SET NOCOUNT ON;

    SELECT * FROM orders WHERE customer_id = @customer_id;

END

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Step 4: Data Migration

Once your schema is in SQL Server, begin data transfer.

Tools:

• BCP (Bulk Copy Program)

• SSMA (built-in migration functionality)

• SSIS (SQL Server Integration Services)

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Examples:

🔹 Export data from ASE using BCP:

        bcp dbname.dbo.orders out orders.txt -c -S ase_server -U user -P password

🔹 Import into SQL Server:

        bcp newdb.dbo.orders in orders.txt -c -S sql_server -U sa -P password

🔹 Validate row counts:

-- In ASE

SELECT COUNT(*) FROM orders;

-- In SQL Server

SELECT COUNT(*) FROM orders;

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Step 5: Application and Query Adjustments

Update your application logic to align with SQL Server behaviors.

Required Changes:

• Modify connection strings

• Refactor SQL syntax and procedures

• Adapt transactions, dynamic SQL, cursor logic

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Examples:

🔹 Connection String Update:

- jdbc:sybase:Tds:hostname:5000/dbname

+ jdbc:sqlserver://hostname:1433;databaseName=dbname

🔹 SQL Pagination Change:
SAP ASE:

SELECT TOP 5 * FROM orders ORDER BY order_date DESC;

SQL Server:

SELECT * FROM orders ORDER BY order_date DESC

OFFSET 0 ROWS FETCH NEXT 5 ROWS ONLY;

🔹 Transaction Handling:

BEGIN TRAN

-- business logic

COMMIT TRAN

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Step 6: Testing and Validation

Rigorous testing ensures your migration doesn’t break functionality or performance.

Key Tests:

• Functional Testing (stored procedures, application workflows)

• Performance Benchmarks

• User Acceptance Testing (UAT)

• Error log audits

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Examples:

🔹 Test output:

EXEC sp_get_orders @customer_id = 1001;

🔹 Performance profiling:

SET STATISTICS TIME ON;

-- Query execution

SET STATISTICS TIME OFF;

🔹 Data mismatch detection:

SELECT * FROM orders

EXCEPT

SELECT * FROM orders_backup;

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Step 7: Deployment and Post-Migration Optimization

With tests cleared, deploy to production and begin continuous improvement.

Final Tasks:

• Monitor queries and CPU usage

• Configure backups, alerts, failover strategies

• Provide team training

• Review and improve indexing, execution plans, and query cache

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Examples:

🔹 Find expensive queries:

SELECT * FROM sys.dm_exec_query_stats

ORDER BY total_worker_time DESC;

🔹 Add missing index:

CREATE NONCLUSTERED INDEX idx_customer_id ON orders(customer_id);

🔹 Backup setup:

BACKUP DATABASE newdb TO DISK = 'C:\backups\newdb.bak';

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Conclusion

Migrating from SAP ASE to SQL Server provides tangible value—but it’s not a simple copy-paste job. It involves:

• Careful analysis

• Strategic tool selection

• Tactical application rewrites

• Thorough testing

• Proactive post-deployment tuning

Using this guide and the built-in examples, your migration team can deliver a robust, high-performance SQL Server implementation.