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May 15, 2024

Hazelcast Showcases Real-Time Data Platform at 2024 Gartner Summit

LAS VEGAS, May 15, 2024 — Hazelcast, Inc., the company that enables instant action on all data, recently announced that it is a Silver Exhibitor at the on-going 2024 Gartner Application Innovation & Business Solutions Summit in Las Vegas. Hazelcast is showcasing its high-performance, resilient and scalable unified platform as a core data infrastructure component for real-time and AI application workloads.

Gartner Application Innovation & Business Solutions Summit focuses on the future of applications, where new user experiences, new capabilities and new platforms are required to maximize the business value of existing and new application investments. The Summit connects analysts, technology leaders, and vendors for sessions, demos, and conversations on new and emerging technologies for application modernization initiatives.

Hazelcast at the 2024 Gartner Application Innovation & Business Solutions Summit

During Gartner’s three-day event, the Hazelcast team (booth #119) is meeting with CTOs, application architects and engineering leaders to discuss innovative approaches to solving application modernization challenges, including the need for fast data access and compute for data-intensive, mission-critical applications and AI workloads.

Attendees can meet with the Hazelcast team to learn more about its unified real-time data platform and how it equips businesses with a competitive edge that delivers improved performance and strong data consistency at a lower total cost of ownership, which is an important requirement across many industry use cases, such as financial services, adtech, sports betting and gaming, video gaming, etc.

Topics include:

Core tenets of application modernization and the difference between traditional AI/ML capable of learning in real-time.

  • How to achieve smarter AI and context-aware applications through integrated, stream-based data storage and processing.
  • Approaches to achieving the performance, resilience, and scale necessary for modern applications to maximize IT investments without incurring developer overhead.
  • Working examples of real-time, data-rich intelligent applications, including real-time payment processing and fraud detection with real-time ML.

According to Gartner1, “Software engineering leaders are under continuous pressure to adopt modern architectures and technologies. To do this well, they need to know which trends have the greatest potential impact for their digital business efforts within an actionable planning horizon,” said Joachim Herschmann, VP Analyst at Gartner.

A recent survey revealed that 40% of financial services companies lack the proper data infrastructure, and 35% lack the appropriate technology infrastructure for AI initiatives2. Hazelcast Platform is a unified real-time data platform encompassing fast data storage, in-line compute, and data access for real-time and AI applications. This unified approach simplifies application architectures, significantly reducing total cost of ownership (TCO) from prototyping and designing (Day 0) through developing and deploying (Day 1) and maintaining, monitoring and optimizing applications (Day 2).

Last month, Hazelcast released its latest version, Hazelcast Platform 5.4, setting new industry standards in strong data consistency and performance for data-intensive, mission-critical workloads. Among the new features in the release are an advanced CP Subsystem for strong data consistency and a thread-per-core (TPC) architecture, which delivers a 30 percent performance improvement on large workloads.

To learn more, meet the Hazelcast team at booth #119 or schedule a personalized demo.

About Hazelcast

The world’s leading companies trust Hazelcast and its unified real-time data platform for mission-critical and data-intensive workloads that require high performance, resilience, and scale. Customers such as JPMorgan Chase, Volvo, New York Life, Target, and Domino’s rely on the Hazelcast Platform for application modernization initiatives and AI/ML deployments.

Source: Hazelcast