Database Migration
There are few common reasones to migrate database,
Better Performance
Moving to Cloud
Changing Needs
Cost Cutting
Hardware Upgrades
Oracle to Postgresql:
Migrating from Oracle to PostgreSQL delivers a drastic reduction in total cost of ownership (TCO) alongside freedom from restrictive commercial licensing.
This migration may take place in Cloud to Cloud, On-premises to On-premises, On-premise to Cloud or Cloud to On-premise.
MSSQL to Postgresql:
Migrating from Microsoft SQL Server (MSSQL) to PostgreSQL eliminates expensive commercial licensing costs, prevents vendor lock-in, and unlocks an open-source ecosystem featuring powerful extensions like PostGIS and pgvector
This migration may take place in Cloud to Cloud, On-premises to On-premises, On-premise to Cloud or Cloud to On-premise.
MySQL to Postgresql:
Migrating from MySQL to PostgreSQL provides superior handling of complex analytical queries, stricter data integrity enforcement, and native readiness for AI and NoSQL workloads. While MySQL is highly optimized for simple, high-speed read/write transactions, PostgreSQL serves as a richer, feature-heavy object-relational database.
This migration may take place in Cloud to Cloud, On-premises to On-premises, On-premise to Cloud or Cloud to On-premise.
MongoDB to Postgresql:
Migrating from MongoDB to PostgreSQL provides stronger ACID compliance, strict data validation at the database layer, and superior performance for complex relational queries and joins. It eliminates the data drift and unmaintainable implicit schemas that often accumulate in large document stores.
This migration may take place in Cloud to Cloud, On-premises to On-premises, On-premise to Cloud or Cloud to On-premise.
In a similar manner, Oracle, PostgreSQL, MSSQL, MySQL, and MongoDB can be migrated both to and from each other.
We specialize in the aforementioned migrations, prioritizing performance to ensure that any performance issues are addressed prior to the final cutover, thereby preventing any degradation in performance after migration. Hence we call it "Performance-Driven Migration"
Database Performance Tunning(Managing through AI and Open Source Technologies)
This shifts the traditional tasks of Database Administrator (DBA) from manual, reactive knob-turning to proactive, autonomous optimization. Instead of a developer hunting down slow queries, an agent scans system catalogs for queries with high cumulative runtimes. Parameter tunning in enterprise database are critical and needs a careful adjustment,
Oracle Database: 300 to 450+ explicit initialization parameters (such as sga_target and pga_aggregate_target), though tens of thousands of hidden/undocumented parameters exist internally.
PostgreSQL: 300 standard parameters configurable in postgresql.conf, grouped into categories like memory, query planning, and WAL.
MySQL: 500+ server system variables (in MySQL 8.0/8.4), controlling everything from InnoDB buffers to connection timeouts.
Microsoft SQL Server (MSSQL): 70 standard advanced server configuration options exposed via sp_configure (e.g., max degree of parallelism, min/max server memory), alongside hidden trace flags.
MongoDB: 60 to 80 configurable mongod server parameters (adjusted via --setParameter or runtime commands), focusing on WiredTiger cache, transport, and diagnostic settings.
We implement compact scripts that function as playable AI agents, serving as an automation service. In any critical production environment, an AI agent is upheld through access control, execution guardrails, data sovereignty, self-healing, and rollback mechanisms. Human errors are mitigated by well-regulated AI agents.
Database Automation
