Coffee Meets Bagel meets Redis Labs to Solve Performance Challenges

MOUNTAIN VIEW, Calif., Oct. 23, 2018 /PRNewswire/ -- Redis Labs, the home of Redis and provider of Redis Enterprise, today announced that dating app Coffee Meets Bagel has turned to Redis Enterprise to dramatically improve its application performance and smoothly scale operations as the company expands internationally and experiences massive user base grows.

Coffee Meets Bagel is a highly curated online dating service. Since its founding in 2012, the dating app provider has grown to more than three million users around the globe. As the business grew rapidly, their existing Cassandra implementation experienced noticeable scalability issues, resulting in partial outages that impacted user experience. As a result, Coffee Meets Bagel turned to Redis Enterprise to deliver consistent high-performance. Redis Enterprise Virtual Private Cloud (VPC) was deployed to increase performance and seamlessly scale across the globe while serving a number of critical functions, including caching, user analytics and real-time data streaming.

"High performance has always been critical to our operations," says Stephen Brandon, Engineering Manager, Infrastructure Operations at Coffee Meets Bagel. "Redis Enterprise's auto-scaling capabilities have eliminated days of manual effort previously required. In addition, we've had no problem achieving 99.99% uptime, and with the implementation of Redis on Flash, we've saved upwards of 40% for the year, without sacrificing latency."

When match recommendations are being pushed to users, Coffee Meets Bagel's applications process upwards of one terabyte of data in an hour. In this fast-paced environment, Redis Enterprise VPC performs several critical roles, including:

• Personalized recommendations: Redis Enterprise provides high-performing in-memory operations that enable Coffee Meets Bagel to generate highly personalized recommendations for its millions of users, and process billions of user matches at high speeds.
• Primary data storage. Redis Enterprise is the primary database for more than two terabytes of user information. Through Redis Enterprise's in-memory processing and backlog queue, Coffee Meets Bagel can store data for later use.
• Fast data ingest. Redis Enterprise's data ingest capabilities seamlessly scale to process upwards of one terabyte of data an hour, including over 300 million exchanged messages and more than one billion matches, without the need for worker throttling.

"Redis Enterprise's multi-faceted capabilities truly shine in its deployment at Coffee Meets Bagel," said Jason Forget, Redis Labs' CRO. "Supporting personalization, data ingest and data persistence at massive scale while maintaining low latency and high availability is difficult for most databases. Redis Enterprise is uniquely suited to serve such complex needs."

For additional details on how Coffee Meets Bagel is leveraging Redis Enterprise, please visit https://redislabs.com/customers/coffee-meets-bagel/.

About Redis Labs
Modern businesses depend on the power of real-time data. With Redis Labs, organizations deliver instant experiences in a highly reliable and scalable manner. Redis Labs is the home of Redis, the world's most popular in-memory database, and commercial provider of Redis Enterprise that delivers superior performance, matchless reliability and unparalleled flexibility for personalization, machine learning, IoT, search, eCommerce, social and metering solutions worldwide.

Redis Labs, ranked as a leader in top analyst reports on NoSQL, in-memory databases, operational databases, and database-as-a-service, is trusted by over 8,500 enterprise customers, including six Fortune 10 companies, three of the four credit card issuers, three of the top five communication companies, three of the top five healthcare companies, six of the top eight technology companies, and four of the top seven retailers.

Redis has been voted the most loved database, rated the most popular database container, #1 cloud database, and the #1 NoSQL in software stacks.

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SOURCE Redis Labs

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