Getting up to speed
Working with VoltDB, Shopzilla significantly boosted the rate at which it can process inventory data and derive actionable intelligence. Higher-velocity updates drive revenues by delivering near-real-time information to consumers and by passing along more highly targeted leads to the thousands of retailers paying Shopzilla on a pay-per-click basis.
On a simple three-node evaluation cluster supporting full durability, Shopzilla achieved 80,000 to 100,000 writes per second with VoltDB. Once fully optimized and in production, that level of performance helped eliminate complicated caching and data pre-loading processes, simplifying Shopzilla's architecture and allowing it to interact directly with the database. The company also used VoltDB's point-in-time snapshot capability as a faster way to export inventory data for further analysis. In addition, Shopzilla gained the ability to filter offers coming into its system, removing duplicates and reducing the transactional load downstream from 2,500 TPS to 650 TPS, allowing the company to save on hardware and operational expenses.
VoltDB's stored SQL procedures allow Shopzilla to identify and fix any errors in application updates before deployment. Shopzilla is also able to constantly update its sales and consumer feedback for online merchants and retail advertisers based on those real-time analytics.
Since switching to VoltDB, Shopzilla has achieved its first milestone of rapid feed ingestion with a five-fold increase in performance. It's the first step in enabling an overall latency reduction for accurate product and pricing information.
This article, "Shopzilla buys into big data for fast meta-shopping," was originally published at InfoWorld.com. Read more of Andrew Lampitt's Think Big Data blog, and keep up on the latest developments in big data at InfoWorld.com For the latest business technology news, follow InfoWorld.com on Twitter.