BioCatch Effortlessly Scales Its Fraud Detection Platform with Redis Enterprise
Customer Company Size
Large Corporate
Product
- Redis Enterprise VPC
- Microsoft SQL Server
- Apache Cassandra
- Apache Impala
Tech Stack
- Redis Enterprise
- Microsoft Azure
- Apache Spark
- Machine Learning
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Cost Savings
- Productivity Improvements
- Customer Satisfaction
- Digital Expertise
Technology Category
- Platform as a Service (PaaS) - Data Management Platforms
- Infrastructure as a Service (IaaS) - Public Cloud
- Analytics & Modeling - Machine Learning
Applicable Industries
- Finance & Insurance
- Software
Applicable Functions
- Business Operation
- Quality Assurance
Use Cases
- Fraud Detection
- Real-Time Location System (RTLS)
Services
- Cloud Planning, Design & Implementation Services
- System Integration
- Data Science Services
About The Customer
BioCatch is a world leader in behavioral biometrics. Its innovative fraud detection technologies are redefining digital identity through unique behavior characteristics such as how a user holds their phone, types, swipes across the screen, or scrolls down the page. As more and more top tier financial institutions and enterprises worldwide adopted the company’s groundbreaking biometrics tracking solutions, BioCatch turned to Redis Enterprise VPC from Redis Labs to overcome the significant database scaling issues it faced as a result of extreme rapid growth. Today, BioCatch relies on Redis Enterprise to service more than 70 million platform end users of its platform with zero downtime, zero operational hassle, and near-zero latency.
The Challenge
Before Redis Enterprise, the BioCatch operations teams were struggling to keep pace with the company’s rapid growth. As the platform reached and then surpassed five billion transactions per month, the issue of scaling consumed everyone’s attention, leaving no resources to focus on new product features. “Version one of our solution was built to go to market very fast,” says Dekel Shavit, BioCatch VP of Operations & CISO. “It wasn’t designed with 70 million users in mind and so efficient architecture and data models weren’t initially top of mind.” But it was clear that a redesigned technology stack needed to be top of mind for the solution’s next incarnation. Of particular priority was decoupling compute and state to make the system more elastic. Session state was being kept across many virtual machines; if a machine fell down, all of its sessions were lost. This configuration was not only proving to be a liability within the context of critical real-time fraud detection, but also very difficult—and expensive—to scale.
The Solution
As BioCatch undertook the much-needed redesign of its technology stack, Redis Enterprise, known for its ease of implementation and exceptionally high performance, became the centerpiece—and remains so today. “Since its implementation more than a year and a half ago, Redis Enterprise has kept latency to an average of less than .96 milliseconds, even at peaks of 40,000 operations per second,” says Shavit. “And it has done so without spikes, a key driver for us, and, incredibly, with zero downtime.” BioCatch uses Redis Enterprise VPC, a fully managed database-as-a-service from Redis Labs. Redis Enterprise VPC is installed inside BioCatch’s virtual private cloud within the Microsoft Azure public cloud. It serves an average of three terabytes of data and 200 million keys at any given moment to the many microservices that power the company’s applications and is currently the only stateful component of BioCatch’s redesigned stack. The biometrics company runs a few other databases alongside Redis Enterprise including Microsoft SQL Server, Apache Cassandra, and Apache Impala, but has been migrating more and more data into Redis Enterprise. “We looked to Redis Enterprise for caching initially, but quickly discovered that it is really good as a database—not just a simple database, but also a system configuration database,” says Shavit. “Most of our data now resides in Redis Enterprise because it’s always available, and it’s always highly responsive no matter how you query it.”
Operational Impact
Quantitative Benefit
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