Mactores Application and Database Modernization on AWS

Mactores Application and Database Modernization helps enterprises escape high-cost legacy database platforms and modernize the application code, ETL pipelines, APIs, and dependencies that keep those platforms hard to retire. We help customers move from Microsoft SQL Server, Oracle, Teradata, IBM DB2, SSIS, and EC2-hosted monoliths to AWS-native architectures using Amazon Aurora, Amazon RDS, AWS Glue, Amazon ECS, Amazon EKS, AWS Lambda, and AWS Fargate.

Unlike migration-only approaches, Mactores modernizes the database and application estate together. Aedeon, our proprietary agent platform, along with Mactores CodeConverter and CodeAnalyzer, accelerates dependency discovery, schema conversion, T-SQL and PL/SQL conversion, embedded SQL remediation, ETL re-platforming, parity test generation, validation, and cutover planning. Forward-deployed engineers own architecture, performance tuning, operational readiness, and production cutover.

The Modernization Challenge

Enterprise leaders face escalating Microsoft SQL Server and Oracle Enterprise Edition licensing fees, EC2-based databases that cannot elastically handle peak-season volumes, undocumented stored procedures and SSIS packages, application code tightly coupled to vendor-specific SQL syntax, and 10–20 years of accumulated technical debt. These challenges slow innovation, increase operating cost, create security exposure, and make every production change risky.

Our Approach

Immersion Day and Discovery: We map current state across databases, applications, ETL packages, downstream integrations, and dependencies, surfacing technical debt and licensing exposure.

Architecture Workshop: A structured 2-day workshop produces a definitive migration scope, phased sequencing plan, near-zero-downtime cutover strategy, and TCO analysis.

Proof of Concept: A focused 4-week PoC validates schema conversion, data migration, stored procedure conversion, performance benchmarking, and ETL migration on a representative subset of the environment.

Agent-Native Execution: Aedeon, CodeConverter, and CodeAnalyzer accelerate schema conversion, stored procedure conversion, application code remediation, ETL re-platforming, parity test generation, and validation. Mactores engineers lead architecture, implementation, performance tuning, and cutover.

Near-Zero-Downtime Cutover: AWS DMS Change Data Capture replication keeps the AWS target synchronized with the legacy source during testing and validation, enabling production cutover in hours, not days.

AWS Services We Build On

Databases: Amazon Aurora PostgreSQL Serverless v2, Amazon Aurora MySQL, Amazon RDS for PostgreSQL, MySQL, SQL Server, MariaDB, and Oracle, Amazon DynamoDB, Amazon DocumentDB, Amazon ElastiCache.

Migration Tooling: AWS Database Migration Service (DMS), AWS Schema Conversion Tool (SCT), AWS Application Migration Service (MGN), AWS Migration Hub, AWS DataSync, AWS Snowball.

Application Compute: Amazon EC2, Amazon ECS, Amazon EKS, AWS Lambda, AWS Fargate, AWS App Runner.

ETL and Integration: AWS Glue (PySpark Jobs, Workflows, Data Catalog), AWS Step Functions, Amazon EventBridge, Amazon MQ, Amazon SQS.

Security and Operations: AWS IAM, AWS KMS, AWS Secrets Manager, AWS CloudTrail, Amazon CloudWatch, Amazon VPC, AWS Config, AWS Backup.

Migration Patterns We Cover

MSSQL on EC2 or on-prem to Amazon Aurora PostgreSQL Serverless. Oracle to Aurora PostgreSQL or Aurora MySQL. PostgreSQL or MySQL on EC2 or RDS to Aurora. Greenplum, Netezza, or Teradata data warehouses to Amazon Redshift. SSIS, Informatica, and DataStage ETL to AWS Glue. Java Hibernate, .NET Entity Framework, and Spring application code remediation for PostgreSQL. Lift-and-shift on EC2 to containerized ECS or EKS, or serverless Lambda.

Proven Outcomes

Enterprise payments modernization: 80% database TCO reduction (~$720K annual savings) by migrating MSSQL-on-EC2 to Aurora PostgreSQL Serverless. 4x query throughput improvement. 70% reduction in DBA operational effort. 60% code optimization across stored procedures and application source code. 16-week production migration with under 4 hours cutover window and zero data loss. 15+ years of technical debt retired.

Engagement Model

Mactores supports phased modernization engagements that can begin with assessment and roadmap development, then expand into proof of concept, implementation, validation, cutover, and operational readiness. Final scope, timeline, deliverables, and pricing are defined through a private offer and statement of work based on source platforms, application complexity, database size, stored procedure volume, integrations, downtime requirements, security needs, and target AWS architecture.