Customer Case Studies

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Concur added a high-speed caching layer with Couchbase to speed up the performance of its numerous business application products.

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Concur

Concur implemented a large Couchbase Server cluster, utilizing the Enyim (.NET) client for the web tier and the spymemcached (Java) client for the middle tier. They were impressed with the simplicity with which they could set up, configure, and scale the cluster. For example, the ability to use a single solution across multiple tiers and languages was a huge win for Concur and made Couchbase a more attractive option than other solutions, which required different implementations for each. Using the recommended reverse proxy setup, there’s just a single IP address for configuring REST connections and monitoring across multiple tiers. Couchbase's cluster management capabilities give Concur the ability to scale out their cluster with zero downtime. They also get the added benefit of zero configuration management when adding or removing nodes from their cluster because both the .NET and Java clients are automatically updated when there is a topology change, ensuring smooth and consistent growth of the Couchbase cluster across the entire environment.

Equifax uses multi-dimensional scaling to provide 5-millisecond response times for users of 1.5 billion constantly changing records.

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Equifax

In the U.S., the financial data company Equifax is best known for providing credit scores used by lenders to make consumer loans. When the Federal National Mortgage Association announced major changes in their credit score requirements, Equifax had to act fast. The company decided to switch to a NoSQL database to get the high performance and scalability needed to provide 5-millisecond response times in a system handling 1.5 billion constantly changing records. After evaluating Couchbase against MongoDB and Redis, Equifax decided Couchbase was the clear winner. The most important differentiator was Couchbase’s Multi-Dimensional Scaling, which Equifax uses to scale individual workloads separately. Equifax was also able to quickly and easily implement disaster recovery using Couchbase’s cross datacenter replication (XDCR) and master-master replication scheme. The operations team was sold on the power of the Memcached protocol and RESTful API for system monitoring and management. Developers liked the simplicity and flexibility of N1QL, Couchbase’s SQL-based query language for JSON. By replacing Hadoop with RxJava, the development team was able to process 300+ million documents in 40 minutes. Couchbase’s technical support team sealed the deal by partnering closely with Equifax during the intense 24/7 production cycle in the months prior to launch.

FICO chose Couchbase over MongoDB™ to provide superior speed, scalability, and availability for the world’s #1 fraud detection platform.

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FICO

Powered by Couchbase, FICO’s fraud detection platform is #1 in the world and scores 65% of the world’s credit/debit cards. Downtime means fraud and lost revenue for the company, so when FICO was chosen to provide credit checks, fraud screening, and targeted offers for new telecommunications customers both in-store and online, it needed a NoSQL database that could deliver high availability alongside high transactional volume. Couchbase was chosen over Cassandra and MongoDB for speed, scalability, availability, and persistence to support large XML objects.

Intuit supports 250K peak-season TurboTax users at the same time using a microservices architecture built with Couchbase on AWS.

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Intuit

Intuit’s TurboTax is the best-selling online tax preparation software, serving millions of customers annually. During peak tax season the application has to support over 250,000 users at once with an average session time of 35 minutes. When TurboTax’s monolithic architecture couldn’t keep up with increasingly complex requirements, Intuit partnered with Couchbase to move it to a microservices architecture on AWS. Couchbase provides the built-in high availability and data replication TurboTax needs for dependable performance and 24/7 uptime – plus the unmatched flexibility developers need for testing and deploying updates on the fly.

PayPal manages over 1B documents and 10TB of data with Couchbase while processing millions of user analytics updates per minute.

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Paypal

In 2013, PayPal, a global leader in online payments solutions, took on NoSQL for several use cases. They initially leveraged Couchbase for their Media Network Advertising pipeline and applied Couchbase to build cross-channel audience analytics in profiling, segmentation, identity mapping and more. By 2014, the company was managing over 1 billion documents and 10 terabytes of data with Couchbase. PayPal extended Couchbase use into analytics for user information, processing millions of updates a minute in conjunction with Kafka and Hadoop.

Revolut combines machine learning with Couchbase’s speed, agility, and scalability to monitor card transactions and reduce fraud.

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Revolut

The UK fintech company Revolut developed Sherlock, a machine learning-based fraud prevention system, to counter the growing threat of financial fraud. Sherlock continuously and autonomously monitors card users’ transactions, and if it finds a suspicious transaction it sends the user a push notification for their approval. Revolut selected Couchbase because of its inherent architectural advantages – including speed, agility, and scalability – that address the ever-changing data needs of users and merchants.

Wells Fargo, the world's second-largest bank, uses Couchbase to monitor 50 million transactions per day for fraud in real time.

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Wells Fargo

Wells Fargo, the world's second-largest bank by market capitalization and the fourth largest bank in the U.S. by total assets, uses Couchbase to support its fraud monitoring infrastructure. High performance, high availability, and easy scalability help Wells Fargo monitor each and every transaction for fraud at less than 10 ms per operation for 9,000 reads and writes per second.

Solutions

Catalog and Inventory

Combine product and inventory data in real time and scale to millions of products and requests per second to present the right data at the right time.

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