What is real-time data streaming and how does it impact the live sports betting industry?
Real-time data streaming is the continuous flow of data that allows instant processing and analysis as events happen. In sports betting, it enables operators to offer live odds, detect risks instantly, and deliver dynamic in-play experiences that keep bettors engaged.
This blog explores the state of data streaming in the gaming industry in 2025. With the rapid evolution of casual online games, Esports, social gaming platforms, gambling, and other emerging business models, the demand for reliable, scalable data infrastructure has never been greater.
To stay competitive, gaming companies that offer live sports betting need access to data at the moment that data is created. In addition, businesses need real-time observability across their systems, the ability to launch new features quickly, and seamless integrations with cutting-edge technologies like AI/ML, virtual reality, and cryptocurrency. In short, data streaming enables organizations to ingest, connect, process, analyze, and govern data instantly at any scale. This, in turn, transforms key business operations in the competitive sports betting industry.
The sports betting industry is undergoing a significant technological shift driven by the increasing need for low-latency data pipelines, real-time decision-making, and intelligent automation at scale. As regulatory environments evolve and user demand for in-play betting and instant responsiveness grows, operators are moving away from traditional batch-based architectures in favor of high-throughput, event-driven systems.
At the core of this transformation is Apache Flink® and Ververica. Flink is a stateful stream processing open-source project built to handle unbounded data with sub-second latency and exactly-once semantics. Flink empowers sportsbooks to ingest and process live feeds in real time, enabling immediate odds recalculations, anomaly detection, and contextual personalization with high reliability and fault tolerance. In addition, Ververica, founded by the original creators of Apache Flink, offers a production-grade, enterprise solution that is 100% compatible with Flink and designed to meet the real-time demands of industries like sports betting.
Let’s examine how the integration of Flink and real-time data is redefining operational efficiency, user engagement, and risk management in modern sports betting platforms, and why embracing this architecture is essential for staying competitive in a data-intensive, high-frequency environment.
Technology is undeniably transforming the live sports betting industry, fueling its rapid growth and digital evolution. As of 2025, there are over 24,000 registered sports betting businesses globally, spanning both online and traditional platforms. However, a substantial and increasing portion of these businesses operate entirely online, reflecting a broader shift toward digital engagement.
Currently, Statista.com values the sports betting market at approximately $53.78 billion, with forecasts suggesting growth to $93.31 billion by 2030. Innovations such as advanced mobile applications, machine learning, and artificial intelligence have significantly contributed to this continued growth.
Figure One: The sports betting market size is forecasted to increase significantly over time.
Additionally, cloud computing has provided the scalability necessary to sustain and further propel industry gains. Crucially, the migration from traditional RESTful APIs and batch processing to real-time streaming platforms has enabled the delivery of actionable insights in seconds or milliseconds rather than minutes or hours, unlocking substantial operational and competitive advantages for companies that offer live betting apps, websites, and the like.
So, what is real-time stream processing, and why does it matter? Real-time stream processing is a computing approach that continuously processes and analyzes data immediately as it arrives, rather than storing it for later analysis. Unlike traditional batch processing, which collects data into batches and processes them at scheduled intervals, often minutes or hours later, real-time streaming processes data instantly, enabling immediate insights and actions.
In the sports betting industry, where odds change by the second and bettors expect immediate responses, batch processing falls short. The delay inherent in batch methods leads to outdated odds, missed betting opportunities, and increased risk exposure. Real-time stream processing technologies, like Flink, ensure betting companies can dynamically adjust odds, detect suspicious patterns instantly, protect against fraud in the moment, and deliver a more engaging, responsive betting experience, which is essential for profitability and competitiveness.
Figure Two: For many use cases specific to sports bettering, the value of data deteriorates quickly over time.
Apache Flink behaves as an engine powering real-time data decisions. It’s an open-source project built to process endless streams of information the moment they happen. Designed to process data quickly, it is ideal for scenarios where milliseconds matter, like fraud detection, live recommendations, or adjusting sports betting odds on the fly.
When compared to other stream processing tools, Flink stands out in the crowd. For example, Kafka Streams is great for lightweight use cases within the Kafka ecosystem, but Flink brings heavyweight power to the table, able to handle complex logic, massive scale, and stateful processing across any data source.
Spark Structured Streaming is appropriate for batch-minded teams just dipping into streaming use cases, but its micro-batch architecture can introduce lag while Flink stays truly real-time throughout. Finally, while Apache Storm helped pioneer the space, Flink is a modern upgrade, as it is fault-tolerant, expressive, and ready for production-grade workloads.
In the fast-paced world of online gambling, timing is everything. The ability to instantly update odds based on live events, like a sudden player injury, a red card, or a game-changing play, can make the difference between profit and loss. Using a real-time data solution like Flink and Ververica, sportsbooks can analyze incoming data streams and adjust odds within milliseconds, keeping them accurate and reflective of current game conditions. This speed not only improves the competitiveness of the business, allowing it to stay ahead of market shifts, but also builds trust with bettors who expect fair, up-to-date lines. The result is a smarter, faster betting experience that drives engagement, reduces risk, and gives operators a significant edge.
One of the most well-known and documented real-time data use cases is fraud detection, where the ability to correlate events, maintain per-user state, and react within milliseconds allows businesses to flag anomalies before they escalate.
Rapid detection of unusual patterns is critical to prevent fraud and minimize risk in the sports betting industry. Utilizing Flink, operators can monitor thousands of bets in real time, identifying suspicious activities like sudden spikes in bets on obscure matches or abnormal wagering behavior across accounts as it happens. This speedy responsiveness allows betting platforms to take immediate action, such as flagging accounts or suspending markets before damage occurs.
For betting operators, this translates into stronger security, smarter risk controls, and a competitive edge built on real-time insight. Figure Three below illustrates real-time fraud detection and response time via Ververica’s Unified Streaming Data Platform, built by the original creators of Apache Flink.
Figure Three: Real-time fraud detection using Ververica’s Unified Streaming Data Platform, built by the original creators of Apache Flink.
Related to fraud and anomaly detection, Flink also enables dynamic risk exposure management by continuously analyzing betting volumes and liabilities. Sportsbooks can then instantly adjust limits or odds to balance risk, ensuring they stay profitable and protected even in volatile, high-stakes betting environments.
User engagement is heavily influenced by timing and personalization. Flink empowers operators to deliver real-time notifications, targeted offers (using live odds or live in-play betting), and personalized betting suggestions based on a user’s behavior, preferences, and live game data. Whether it's a push alert for a trending in-play bet or a custom promo triggered by a user's favorite team taking the lead, businesses can enable these dynamic betting interactions to happen within seconds.
This level of immediacy not only keeps bettors actively engaged but also creates a more dynamic and tailored experience. By responding to live events and user actions in real time, sportsbooks can boost conversion rates, increase session times, and foster stronger customer loyalty all through the power of streaming data.
In-play live betting thrives on immediacy, where every second presents a new opportunity or risk. By harnessing data as it's generated, operators can offer dynamic betting that evolves with the flow of the game. This can include adjusting lines, introducing new markets, or closing bets at just the right moment.
Figure Four: Dynamic dashboard powered by real-time data.
Real-time analytics and customer 360 views also open the door to smarter decision-making behind the scenes. By continuously monitoring how users interact with the betting platform, what markets they favor, how quickly they place bets after certain game events, or how they respond to odds changes, operators can uncover meaningful patterns in bettor behavior. These insights help anticipate shifts in demand, such as increased interest in a specific team, sport, or type of wager during certain scenarios.
Instead of relying on outdated, reactive insights, advanced real-time platforms (like Ververica’s Unified Streaming Data Platform) can leverage machine learning models to generate predictive insights. For example, based on historical data and current trends, systems can forecast which types of bets are likely to spike in popularity during key moments, or identify high-value users who may respond positively to a specific offer. This enables operators to act before trends fully materialize, proactively adjusting odds, launching timely promotions, or even limiting exposure on risky bets. By combining live data with predictive intelligence, operators can optimize engagement, reduce risk, and stay ahead of market shifts in a way that batch-based systems simply can’t match.
Modern betting relies on fast, efficient data pipelines to stay competitive, especially when handling thousands of real-time events per second. With Flink, operators can drastically reduce latency by processing data at the moment it arrives, eliminating delays introduced by traditional batch systems. This real-time approach not only ensures that live odds, user actions, and market insights are handled instantly but also streamlines the flow of information across systems.
By consolidating multiple processing layers into a single, unified pipeline, businesses can:
Flink’s ability to dynamically allocate resources and maintain performance under fluctuating loads means operators can deliver a high-speed experience without over-provisioning, making your tech stack leaner, faster, and more cost-effective. Proven at scale by global companies1 like Alibaba, Uber, Netflix, and Booking.com, Flink and Ververica already demonstrate the ability to handle billions of events per day with sub-second latency. For the sports betting industry, this means delivering a high-speed, cost-effective experience that adapts seamlessly to peak loads and real-time demands.
Several real-world implementations highlight how real-time data is driving innovation in the betting and real-time analytics industries1. Here are just a few:
Beyond betting, companies like Booking.com currently use Ververica to process billions of events per day, powering features like recommendations, alerts, and fraud monitoring, while also solving customer 360 and personalization use cases.
These implementations demonstrate the importance of combining low latency, scalability, and stateful processing to solve critical, high-volume challenges in sports betting. Next, let’s explore how Ververica’s solution specifically supports these use cases.
Built to be 100% compatible with open source Flink, Ververica’s Unified Streaming Data Platform offers a production-grade, enterprise-grade solution designed for the real-time demands of industries like sports betting. In addition to the robust data streaming found in Flink, Ververica includes advanced features that are critical for powering live odds adjustments, including:
In addition, Vererica’s Unified Streaming Data Platform is powered by VERA, a high-performance cloud-native engine that powers real-time data decisions. VERA is built to process endless streams of information the moment they happen, while incorporating historical data into the stream as well. While built using best-in-class open source Flink technologies, Ververica is also lightning-fast (up to 2x+ faster than OS Flink), and is designed to support real-time use cases like fraud detection, live recommendations, or adjusting sports betting odds instantly.
While sports betting use cases heavily rely on real-time data, Ververica offers both batch and real-time data speeds, in addition to being fault-tolerant, expressive, highly scalable, and ready for enterprise-grade workloads. And while Flink itself is already incredibly powerful, Ververica takes this further: providing operational support in addition to offering enterprise-grade security and expertise that is unavailable in any open-source community project.
Armed with commercial support and tools built by the minds behind Flink itself, Ververica enables sportsbooks to run low-latency, high-availability systems with ease and confidence, all at lightning speed. This powers use cases like instant odds recalculations, real-time fraud detection, and personalized user experiences, with enterprise-grade reliability and fault tolerance.
Figure Five: Ververica’s Unified Streaming Data Platform allows you to connect, process, analyze, and govern your data from any source to any sink.
As the sports betting industry continues to evolve, the role of real-time data is becoming increasingly central to its success. Technologies like Flink and solutions like Ververica’s Unified Streaming Data Platform not only enable operators to process and react to live data with unprecedented speed but also lay the groundwork for smarter, more personalized, and more secure betting experiences.
From dynamic odds adjustments to predictive modeling and fraud prevention, Flink and Ververica help operators to make informed decisions in real time, turning data into a competitive advantage. Looking ahead, the integration of emerging technologies such as real-time AI models, contextual personalization, and edge computing will further enhance the capabilities of streaming data systems. As these innovations mature, the future of sports betting will be defined by even faster insights, richer user engagement, and more adaptive, intelligent platforms, all built on the foundation of streaming data.
1 This blog post is based on publicly available information. It is not affiliated with, endorsed by, or sponsored by any of the companies mentioned. All company names and trademarks belong to their respective owners.