Database Migration & Simplification

The company, operating with a 40-year-old Oracle database infrastructure, faced challenges in scaling, redundancy, and query optimization. To modernize, we migrated their relational data to a NoSQL MongoDB solution, simplifying data structures, normalizing layers, and optimizing query performance. We implemented a resilient MongoDB cluster with redundancy across regions, automated backups, and ETL processes. The result was a seamless migration, leading to a 60% increase in application efficiency and enabling the company to scale operations effectively across multiple business lines.

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Sunnyvale

Location

Plug and Play

Financial

Industry

Challenge

The company, with over 40 years in the industry, had a legacy Oracle database infrastructure that was central to its operations. The database was heavily reliant on relational models, with complex GoldenGate configurations managing replication between various tables. As the company looked to modernize its technology stack and improve operational efficiency, it faced challenges in scaling, redundancy, and query optimization with its existing setup.

Solution

Our database team conducted a thorough analysis of the existing Oracle databases and created comprehensive ER diagrams to map out the relationships between the tables. After evaluating the company’s needs, we proposed migrating to a NoSQL MongoDB solution. This transition involved simplifying the relational structure, normalizing data layers, and reconfiguring how data was stored to take advantage of the flexibility of MongoDB.

We implemented a distributed MongoDB cluster with higher redundancy across multiple regions and scheduled automated backup jobs to ensure data integrity. Our team also handled the ETL (Extract, Transform, Load) processes, facilitating a seamless migration from the development environment to production. Following the migration, we optimized query performance by indexing the MongoDB collections, leading to a 60% increase in application efficiency. This transformation enabled the company to scale its operations across various lines of business effectively.

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Discover Our Approach

Legacy Database Analysis and ER Diagram Mapping

We meticulously mapped out the relationships within the legacy Oracle database and identified areas for optimization during the migration.

STAGE 1

STAGE 2

Data Migration to NoSQL

We transitioned the relational data to MongoDB, simplifying and normalizing the database layers to align with NoSQL best practices.

High-Availability MongoDB Cluster

We implemented a resilient MongoDB cluster with redundancy across regions, ensuring data availability and fault tolerance.

STAGE 3

STAGE 4

ETL and Automated Backups

ETL processes were developed to migrate data from development to production environments, along with scheduled backup jobs for data integrity.

Query Optimization and Indexing

We optimized the performance of the MongoDB collections by implementing targeted indexing strategies, resulting in a 60% improvement in application efficiency.

STAGE 5

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