From Hazelcast Customer to CTO: Why I Joined Hazelcast
Instant is the new normal. Instant payments. Instant risk assessment. Instant offers. Instant action. Leading companies are leveraging streaming data to take action that meets their business and customers’ needs in an instant.
For years, I’ve led teams and projects behind some of the largest and most complex financial services systems. It’s been a privilege to be on the frontline of innovation, especially now, with the added benefit of architecting platforms to facilitate artificial intelligence AI and ML. The electronic trading platforms I’ve architected and managed, such as transaction banking platforms or, more recently, financial crime transaction monitoring platforms, move at high speeds and improve a company’s security posture.
But, taking action based on new events is complex, and the ability to better inform that action with context from historical data is even more complex. Making the process reliable, secure, and scalable adds additional layers upon layers.
That’s why I was thrilled to find Hazelcast about a decade ago, though I wish I had found it sooner. I’ve seen the technology’s capabilities when it comes to low latency, high availability, speed, cost, and ease of use.
Hazelcast’s unified real-time data platform is bringing a new level of speed and reliability to companies, not just in financial services but in ecommerce, retail, hospitality, technology, gaming, transportation, telecommunications, manufacturing, and more. And it’s simplifying the equation with a unified platform.
Helping Companies Move Data from Burden to Benefit
That’s why I’m here as CTO. Hazelcast is uniquely positioned to support companies in taking informed, immediate actions on data in motion with simplicity. I am focused on taking the burden off customers’ engineering teams and positioning Hazelcast as a single platform to advance real-time capabilities. In return, customers will see a faster time to market and lower total cost of ownership (TCO).
When looking at what’s next, Hazelcast enables companies to deploy machine learning models with real-time data for fast, efficient predictions and optimal performance in AI, event-driven, and many other use cases.
Whether starting from scratch or modernizing existing tech stacks with the ability to pull off instant action, Hazelcast reduces the complexity element of the equation. It retrieves live data from databases, data lakes, applications, devices, and message brokers like Apache Kafka, Apache Pulsar, AWS Kinesis, or RabbitMQ. It then transforms raw, high-volume data streams into business events and actionable insights, making them easily consumable by applications, dashboards, and databases.
From fraud detection to dynamic offers to security, its unified real-time data platform enables a sophisticated real-time data pipeline that meets the most demanding throughput, latency, and performance requirements.
No More Getting It Wrong
This is all great news for the enterprise and customers.
With data and the technology that powers it touching every aspect of a company, job duties and expectations are distributed and don’t always align with a team’s skillset or technical capabilities. With a world-class and proven solution like Hazelcast, enterprises won’t run the considerable risk of getting it wrong.
It reduces the number of separate software components in your real-time architecture, resulting in accelerated development and deployment of applications. For example, most retail stores rely on shipping companies to distribute their products. Similarly, they can rely on a stream processing company to handle their streaming data architectures, enabling them to focus on their core business value and competitive advantages in retail.
I’ve seen teams try to patch together technology for years to improve the speed of data coming in and action going out. They add more and more infrastructure and the more they have, the more risk they have, too. Teams of engineers are devoted to months or years building technology that is slower to market, requires constant monitoring and upkeep, and lags in failure recovery, security, and more. And, they struggle maintain the targeted TCO due to the amount of time involved in deploying, managing, and upgrading such systems.
Hazelcast not only collects streaming data but also processes that data. At the same time, the platform enriches it with historical data in an ultra-fast data store to inform the right instant action at the right time. From growth demands to unexpected load spikes, hardware failures of multitudes of components, downtime, and ongoing administrative tasks, Hazelcast alleviates these challenges and hides the complexity so that companies can get it right, all within a single platform.
This unified capability is unique in the industry, and it’s what attracted me to Hazelcast as a customer and now as its CTO. Our platform is fast, scalable, and companies find it pays for itself.
Technology to Unlock the Full Power of Data
It was a rare opportunity for me to work on the projects I led across financial services. This is another rare opportunity to be part of the team empowering companies to finally unlock the full potential of their data.
Today, we are swiftly approaching an era where traditional coding has become obsolete. No-code, low-code, generative AI and others like it will produce our desired results on command without needing to understand the processes that got us there. It’s not that these processes are gone, they are just seamlessly running in the background.
With Hazelcast’s unified real-time data platform, I am looking forward to bringing a similar level of simplicity to companies’ data-driven initiatives and harnessing the power of instant action on a global scale.
I discovered my passion for computers and the endless possibilities they offered through coding at age six when my brother brought home a computer. Today, I believe my six-year-old self would be immensely proud of what lies ahead.
To learn more about me, read the news announcement: Hazelcast Announces Adrian Soars as Chief Technology Officer.
