Scale Look-to-Book Ratio for Online Travel Agent System
A large international tour operator (the “operator”) provides 24-hour services to its travel agents and Internet shoppers on HPE NonStop servers. Utilizing the Internet, the tour operator’s business grew and look-to-book ratios increased several-hundred fold (from 30:1 to 700:1).
The search query volume carried such a heavy load (up to fifty times the original query load) that the system ran out of capacity. The operator recognized that booking activity evolved into approximately 99% complex queries and 1% simple writes. They needed to scale-out the query system to a multi-node, distributed solution based on commodity hardware.
Additional Asymmetric Capacity Expansion Architecture Notes
- This is similar to a “master-subordinate” architecture
- The master-booking node is hosted on an HPE NonStop server, which is connected and synchronized with any number of scalable NonStop and Windows query nodes via HPE Shadowbase data replication
- The key structure on the master-booking node remains optimized for OLTP (online transactional processing) access (“skinny” keys), and the key structure on the query node is optimized for query (“fat” keys).
- Data from the master-booking node is also replicated to Windows servers running SQL, which supports a large Operational Data Store (ODS) application.
- This read-only function is offloaded from the master-booking node to the commodity Windows hardware, since travel agents and Internet travel companies use the query nodes to look-up vacancy, seat availability, etc.
- The outsource provider’s application is configured (no application modification was required) to perform all queries against the query nodes, yet still apply the booking transactions to the master booking node.
- Scales queries to handle varying (and very large) query volumes
- The entire database resides on each of the read-only nodes, essentially allowing the provider to scale the application across multiple systems to handle unpredictable query volumes
- Additional commodity hardware can be added as query nodes to scale with increasing query load
- Reduces Total Cost of Ownership (TCO) by leveraging commodity systems for Internet queries
- Increases availability with characteristics similar to an active/active architecture
- Introduces disaster recovery capability for the NonStop master node
- If the NonStop master-booking node fails, the “look node” can act as a backup
HPE Shadowbase Products of Interest
- HPE NonStop Shadowbase Basic Data Integration Software (BE443AC/QSA51V6)
- HPE Shadowbase Basic Application Software 1-8 core or 9+ core (WSA51V6T1/T2)
Contact us or your HPE Shadowbase representative, and learn how Shadowbase software will benefit you.
Case Study: Large International Tour Operator Uses HPE NonStop to Optimize Look-to-Book Processing
White Paper: HPE Shadowbase Streams for Data Integration
Solution Brief: HPE Shadowbase Data Replication Solutions