With more than 46,000 GitHub stars, 18,000 forks, and 430 contributors, Redis is an incredibly popular open source project supported by a vibrant community.
But developers don’t just use Redis, they love it. Stack Overflow’s annual Developer Survey has ranked Redis as the Most Loved Database platform for four years running! Designed for the cloud-native world and created by the makers of open source Redis, Redis Enterprise maintains the simplicity and high performance of Redis while adding enterprise-grade performance, availability, scalability, and security capabilities across hybrid, multi-cloud, and global deployments.
Given all that love and all that power, you may be wondering: what do developers actually build with Redis Enterprise? It turns out that application developers look to Redis Enterprise for a long list of critical use cases in industries ranging from gaming and retail to IoT networking, travel, and financial services. Let’s take a closer look at five representative examples:
Soaring from growth in online transactions, digital identity threats, cybercrime, and customer fraud, online fraud is a $20 billion problem that just keeps getting worse and worse, especially for financial services companies. According to Bitglass’ 2019 Financial Breach Report, a hefty 62% of all breached data came from the finance industry. The increased complexity, volume, and sophistication of threats require more advanced fraud detection methods to keep up with malicious actors and protect your business.
Because traditional data platforms often struggle to keep up with the speed, scale, and complexity of modern online transactions, making it difficult to detect and stop fraud in real time, finserve companies rely on Redis Enterprise in many different ways.
BioCatch, an Isreali digital-identity company that uses groundbreaking biometrics tracking to stay ahead of the fraudsters, is a great example. As the company’s business grew rapidly to 70 million users, 40,000 operations per second, and 5 billion transactions per month, the BioCatch team needed a way to deal with significant database scaling issues.
In need of blazing performance, high availability, and seamless scalability from its data layer, BioCatch turned to Redis Enterprise to decouple the compute from the data. After initially considering Redis Enterprise for caching, the team soon realized it would also make a great system-configuration database. BioCatch leveraged many Redis Enterprises features and data structures to create a single-source-of-truth database that serves a variety of mission-critical information across the entire organization. The list includes behavioral, meta, and API data captured during active user sessions; user-behavior-profile subsets; predefined fraudulent-behavior profiles; geolocation data; and system configurations. With 3 petabytes of data, 300 million keys, and 40 databases running on Microsoft Azure, BioCatch relies on Redis Enterprise to serve data for all its microservices. Since deploying Redis Enterprise, BioCatch has had zero downtime, zero issues, and zero operational hassle—giving the team breathing room to focus on strategic projects that serve the company’s core mission.
Don’t miss: Fraud Detection use case
By 2025, the global gaming market is expected to top $250 billion—driven in large part by mobile gaming. But successful mobile games require a great user experience, which can post significant infrastructure challenges, especially for real-time multiplayer games. Users must be able to quickly launch the game, connect to a server, and collaborate with other online players—any lag or stutter can ruin the experience.
Developers rely on Redis’ low latency to deliver the high performance and virtually unlimited scale that are critical in gaming situations where large volumes of data arrive at high speed.
To serve game elements like graphics, pictures, thumbnails, and music at lightning speed, developers require a robust caching solution. Caching with Redis can reduce the load on datastores such as MySQL while ensuring blazing fast response times. Caching helps provide a responsive user experience, with minimal overhead. Redis is ideal for caching, not just because it’s so fast, but because it includes a variety of data structures and such features as customizable expiration, eviction, intelligent caching, and request pipelining, as well as data persistence and high availability.
Scopely, for example, which makes mobile games like The Walking Dead: Road to Survival, relies on Redis Enterprise for a variety of needs, including leaderboards, API management, and queue workload management.
Don’t miss: 15 Reasons to Use Redis as an Application Cache white paper
The COVID-19 outbreak has forever changed online shopping behavior. Online purchases have increased by 6 to 10 percentage points across most product categories, putting even more pressure on traditional retailers. Modern retail is a constant struggle to make store pages available, keep inventory updated, and personalize experiences—all in real time. According to the latest Retail System Research report, approximately 9 out of 10 shoppers say they will abandon a site if it is too slow. Forced to continually re-invent themselves, retailers rely on Redis in a wide variety of ways, from autocomplete functions to site, catalog, and cart search as well as personalization and overall responsiveness. Increasingly, though, modern multi-channel retailers are turning to real-time inventory systems to optimize their inventory, yield, and supply-chain logistics—and to deliver a better customer experience. But building and maintaining these complex systems is a daunting task for application developers.
Here too, performance is critical. Delayed or inaccurate inventory information can frustrate customers, leading to shopping cart abandonment and order cancellations, lost revenues, higher costs, and brand damage. Redis Enterprise supports real-time inventory management by providing the high availability and super-fast database performance at peak scale developers need, while ensuring data consistency across multiple channels. For example, when giant apparel retailer Gap Inc. wanted to give its e-commerce customers real-time shipping information for each item they added to their shopping carts, the company faced issues around delays and inaccurate inventory information. This created a poor customer experience that inflated costs and eroded brand loyalty.
Application developers at Gap chose Redis Enterprise because its linear scalability and sub-millisecond performance at massive scale helped the team deal with Black Friday-level seasonal peaks—without having to overprovision infrastructure that won’t be used during slower periods. Similarly, other leading retailers, like Staples, for example, rely on Redis Enterprise to underpin complex real-time inventory systems because it powers instant inventory searches, ensures high availability, and handles updates from globally distributed retail channels without compromising latency or consistency.
Don’t miss: Real-Time Inventory ebook
In the era of big data, more and more businesses require software that can instantly collect, store, and process large volumes of data. Yet many of today’s solutions supporting fast data ingest are complex, feature-rich, and over-engineered for relatively simple requirements such as streaming real-time data from the internet of things (IoT) and event-driven applications. In these applications, the key is that the data must be analyzed quickly to make rapid business decisions, and data loss is typically not permissible.
For an example of a fast data ingest use case, look at Inovonics, an industry leader in high-performance wireless sensor networks with more than 10 million devices deployed around the world. For most of its 30-year history, the company considered itself primarily a wireless technology provider. But the rise of big data helped the company realize that the unique sets of data collected by its wireless devices and sensors could also have tremendous value.
Inovonics’ edge platform required a robust set of data-platform capabilities for resilience and performance while minimizing the operational footprint and operating costs. By adopting Redis Enterprise Cloud—a fully automated Database-as-a-Service (DBaaS), Inovonics centralized all its data on Google Cloud, opening up new product offerings in the form of insightful, easy-to-access data analytics.
Inovonics uses Redis Enterprise on its IoT edge devices to push data to its gateways, as well as at the gateways to push data to the company’s virtual private cloud on Google Cloud. On Google Cloud, Redis Enterprise acts as a data ingest, storing the millions of daily messages coming from Inovonics’ sensor networks and providing a central, aggregated, view from which data can be analyzed. Redis Enterprise also stores the application data model so that incoming messages can be correlated with representational information such as sensor location.
Don’t miss: Redis for Fast Data Ingest white paper and Customer Spotlight: Inovonics Delivers Near Real-Time Analytics with Redis Enterprise on Google Cloud webinar
In addition to challenging in-store retail, the COVID-19 crisis has forced technology vendors to re-calibrate and customize their operations and application delivery models. To maintain business continuity at scale without any downtime, businesses need the right tools and techniques to scale their infrastructure and accelerate their application response times.
For example, consider Freshworks, which builds cloud-based suites of business software. Due to extraordinary growth over the past six years, the company was straining the capabilities of its application architecture and development operations. As the company’s database load grew, it struggled to maintain performance. Looking to dynamically scale its cluster without compromising availability, the team also wanted to reduce the burden on Freshworks’ primary MySQL database and speed application responses.
After evaluating NoSQL in-memory databases like Aerospike and Hazelcast, Freshworks chose the high performance and flexibility of Redis. Ultimately, the team chose Redis Enterprise Cloud to ensure high availability and seamless database experience as an infrastructure service for developers.
In addition to using Redis Enterprise as a frontend cache for its MySQL database, Freshworks also uses Redis Enterprise’s highly optimized Hash, List, and Sorted Sets data structures and built-in commands to meter the API requests coming into its Freshdesk software. Redis Enterprise also serves as a persistent store for background jobs, stored on disk. And as Freshworks transitions to microservices, the company has started to separate key workloads out of its monolithic Ruby on Rails web application framework. One of the first microservices to result from this effort is dedicated to authentication, and uses Redis Enterprise as a session store. Finally, Freshworks leverages Redis Enterprise’s powerful data structures including HyperLogLog, bitmaps, and Sets as a frontend database for user analytics.
Don’t miss: Freshworks case study and How Freshworks Scaled from 20 to 500 Million Requests per Day podcast
As developers scramble to quickly deliver new applications and features to users, they are busier than ever. To speed time to market, teams scrambling to leverage multiple data models to get the freedom they need to build apps the right way. They’re also facing pressure to deliver real-time app performance, which for a global user base means keeping the data as close to the users as possible. Created by the makers of Redis—the most loved database four years in a row and the most popular database on AWS two years running—Redis Enterprise lets you work with any real-time data, at any scale, anywhere.
If you’re ready to do the same, start your journey to Redis Enterprise here!
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