NEW YORK – Dec 9, 2021 – VAST Data, the storage software company breaking decades-old tradeoffs, today announced that the digital travel platform, Agoda (a Booking Holdings subsidiary), selected VAST’s Universal Storage as the data science backbone for its big data and machine learning environment. The inherent high-performance and low-latency benefits of Universal Storage will help Agoda deliver more insights and perform more queries in less time for their real-time analytics, supporting thousands of users that are simultaneously searching the website to find the best deals on hotels, flights and other travel reservations.
Customer information and travel supplier data are our most vital assets and we need a data science platform that can easily and cost-effectively scale with our growth,” said Idan Zalzberg, Chief Data Officer, at Agoda. “To help provide our customers with the best value for their travel needs, we require a high-performance big data solution to run our machine learning algorithms, that’s also infinitely scalable to meet our future needs.
Universal Storage allows Agoda to build a cost-effective, private cloud computing environment for Apache Spark and Apache Impala processing that enjoys real-time access to VAST’s S3-compatible fast object storage. Universal Storage disaggregates the compute and storage layers and uses all-flash to accelerate access to shared storage in real-time, providing the scalability, high-availability and low-latency needed to power Agoda’s entire big data analytics and machine learning pipeline.
How VAST Helps Travel Companies Expand Their Horizons
From pricing and availability information sourced from thousands of suppliers, to customer data and trip histories from millions of users, travel sites are tasked with managing massive amounts of dynamic and sensitive data. Historically these organizations were presented with two options: constrained legacy systems that cannot grow with their businesses, or costly and complicated outsourcing to public cloud vendors. Instead, with Universal Storage as the data storage and management foundation, VAST empowers companies like Agoda to cost-effectively manage a constant onslaught of searches and serve up the most compelling and relevant offers in less time.
“Today’s travelers expect a simple and intuitive travel booking experience. Travel sites are hyper-competitive, and if one booking platform can’t produce the right information to the right people at the right time, those people will quickly move along to the next,” said VAST Co-Founder Jeff Denworth. “Agoda is optimizing the customer experience at every layer–from the mobile experience to the data infrastructure foundation. We’re proud to see Universal Storage be selected as that infrastructure foundation that can scale-with Agoda’s success for the next decade and beyond.”
Critical criteria in Agoda’s selection process was infrastructure efficiency. The unique efficiency algorithms that VAST pioneered in Universal Storage, enable revolutionary all-flash storage economics, making it possible for a company to deploy all of their Spark workloads on a scalable, simple and affordable big data platform. Universal Storage is also designed to support an evolving variety of processing paradigms where the multi-protocol aspect of Universal Storage allows Agoda to power their Apache tools with S3 and their Python-based machine learning code from a single unified namespace. By consolidating multiple storage tiers and protocols into a single global namespace, Agoda’s applications will be naturally fast and infrastructure will become both simple and transparent, enabling the company to process all of its data at any scale. VAST’s customer support experience took flight with Agoda, and the VAST Data CoPilot service helped ensure smooth onboarding, systems monitoring and growth planning at each step. It’s this close engineering to engineering partnership and speed to development that separates VAST from the competition. Read this deep dive blog post to understand why customers are choosing VAST Universal Storage to replace their Hadoop Distributed File System.