CUSTOMER
Fortune 100 Investment Bank
CHALLENGE
The development manager at a top global investment bank needed to find a solution to meet the following demands of his organization’s business.
OUTCOME
- The client deployed InterSystems data platform to address both the business and technical challenges.
- The customer management application must support the ability to answer ad-hoc queries about an end customer’s assets
- The same system must support the ability to report traceability to show that trades were in compliance
- The customer management application must scale dynamically and respond to queries in milliseconds, not seconds
- The underlying database must be able to handle big data volumes (TBs) of trade data from across the firm
- The underlying system must scale with increasing demands of velocity, variety, and volume of data
- The system must reduce infrastructure costs
Technical Challenge
The firm’s data was archived into a Hadoop data lake. The architecture had the following limitations:
- The data lake was good for basic historical analysis but could not support real-time, current data streams
- Performance was barely acceptable and had limitations on scaling out
- The application could not provide data drill down for analysis reporting (Hive only supported simple SQL queries, no joins)
- The application could not support more advanced, analytical needs
InterSystems Data Platform
- HDFS was integrated with the data platform to combine terabytes of historical data with current transactions
- The data platform’s persistent store and cached data layer was architected to support the needs of different lines of business. A single deployed reference architecture supported ad-hoc user defined queries with high performance
- InterSystems data platform supports complex SQL queries across all applications while meeting SLAs
- InterSystems data platform for financial services uniquely combines shared-nothing and shared- everything architectures. It proved to be the only option in the market that could provide the required performance at scale
- The reduced costs requirement was met because InterSystems data platform’s ‘cloud-friendly architecture’ does not require specialized hardware. The application could be configured to run (and scale) on commodity hardware
