Project Type: Data Management
Industry: Financial Services
Business Challenge
Managing loads of data from multiple internal/external systems along with security master issues was causing sluggish response times and duplicate records. Looking to increase productivity, this organization sought out a solution that could manage billions of records without impacting performance. Additionally, they wanted something that would enable them to extract information quickly while integrating with existing applications.
Solution
Switching from a traditional relational database to a graph database, they were instantly able to manage billions of records at increased speeds. Utilizing client friendly,intuitive language, the graph database provided a simple, user-friendly data retrieval process that didn’t require exact data format, making it easier for them accomplish tasks.
Approach:
- Install a multi-node instance of OrientDB
- Customize schema of security master for any particular requirements
- Create ingest scripts for two data sources
- Load data from two sources
- Benchmark queries
- Create ingest script of third data source
- Load data from third source
Benefits
- Scalable: Extracting information is simple, intuitive and fast—giving you the ability to handle billions of records without impacting performance. Distributed architecture also supports sharing and replication.
- Increase Flexibility: Adding new sources and types of securities data is very easy. With flexible options, users can tackle even the most complex issues in a simple manner on the fly.
- Boost ROI: Converting to a graph database doesn’t just increase performance—the money saved on reconciliation expenses alone is compelling.