Loading organizations...
Loading organizations...
Hazelcast is a technology company.
Hazelcast provides a unified real-time data platform that combines stream processing with a fast data store, enabling immediate action on streaming data. The platform automates and streamlines application data architectures, delivering real-time capabilities whether deployed on-premises or within cloud environments. Its technical approach focuses on high-performance data operations and intelligent processing to support dynamic business needs.
The company was founded in 2012 by Talip Ozturk and other co-founders, stemming from an insight into the need for reimagined fast data access. They initially focused on developing an advanced in-memory data grid, laying the groundwork for their broader real-time data processing capabilities. This foundational technology aimed to address the growing demand for low-latency data operations.
Businesses across diverse sectors, including financial services, retail, and healthcare, utilize Hazelcast’s platform to enhance operational efficiency and accelerate time-to-market. The company’s long-term vision centers on empowering organizations to leverage real-time data for competitive advantage, transforming raw information into actionable opportunities. They aim to provide scalable, future-proof data architectures that support continuous organizational growth.
Hazelcast has raised $86.5M across 5 funding rounds.
Hazelcast has raised $86.5M in total across 5 funding rounds.
Hazelcast is a technology company that builds the Hazelcast Platform, a unified real-time data platform combining distributed in-memory computing, stream processing, and AI/ML capabilities to power mission-critical applications.[1][2][4] It serves Global 2000 enterprises in financial services, e-commerce, logistics, and other high-stakes sectors, solving the challenges of processing billions of events per second with sub-millisecond latency for real-time decision-making, fraud detection, and AI-driven automation—issues traditional databases can't handle at scale.[1][3][5] Over 50% of the world's largest banks trust it, with tens of thousands of clusters deployed and 23 million server starts monthly, driving strong growth including 300% ARR increase in prior years.[1][3][5]
The platform streamlines development by merging fast data storage, compute, event-driven architectures, and vector search into one runtime, reducing TCO while enabling modernization of legacy apps and new AI applications.[2][6][7]
Hazelcast was founded in 2012 in Palo Alto, California (with early roots possibly in Turkey, given offices in Ankara and Istanbul), initially to reimagine fast data access by creating the world's most advanced in-memory data grid (IMDG)—addressing database limitations in time-sensitive use cases like payments and microservices.[1][3][4][5] The open-source project predates the company, evolving into a commercial platform as founders recognized the shift to real-time data processing before disk storage.[1]
Key milestones include the 2017 launch of Hazelcast Jet, a real-time stream processing engine; the 2022 debut of the full unified platform with ML operationalization; and expansions like Hazelcast Cloud.[1][5][6] Backed by over $60M in venture funding from investors like Earlybird and Capital One, it grew via a strong enterprise customer base including J.P. Morgan Chase, UBS, and Deutsche Bank.[3][5][6] Leadership under CEO Kelly Herrell has emphasized "System of Now" for ultra-low latency at extreme scale.[5]
Hazelcast stands out in operational in-memory computing through these key strengths:
Hazelcast rides the real-time data and AI wave, where enterprises demand instant insights from streaming data amid exploding volumes from IoT, cloud, and edge computing—trends macro forces like digital transformation amplify.[1][5][6] Its timing aligns perfectly with the shift from batch to "System of Now" processing, enabling AI/ML on live data for fraud, personalization, and automation in finance/logistics, where microseconds decide competitiveness.[1][2][7]
Market tailwinds include AI adoption (vector search for LLMs), event-driven architectures, and cloud-native modernization, positioning Hazelcast as foundational infrastructure for Global 2000 apps—much like how Kubernetes standardized orchestration.[2][6][7] It influences the ecosystem by powering economy-moving apps at firms like JPMorgan and Walmart, expanding via partners to accelerate AI deployments globally.[3][5][7]
Hazelcast is primed to dominate as real-time AI infrastructure, with expansions in vector search, partner ecosystems, and mission-critical AI projects signaling momentum toward broader adoption in edge AI and autonomous systems.[7] Trends like agentic AI, 5G/edge streaming, and regulatory demands for low-latency compliance will propel growth, potentially doubling enterprise footprints as TCO savings compound.
Its influence may evolve from niche IMDG leader to ubiquitous platform layer, akin to Redis in caching but with full compute—watch for deeper cloud hyperscaler integrations and IPO paths if ARR sustains triple-digit climbs. This real-time edge cements Hazelcast's role in unlocking business potential from data's "now."[1][2]
Hazelcast has raised $86.5M in total across 5 funding rounds.
Hazelcast's investors include Altair Capital Management, Andreessen Horowitz, Antler, Earlybird Venture Capital, Foundamental, Fuel Ventures, Hoxton Ventures, Iterative, Madrona Ventures, Polygon, Uncorrelated Ventures, Balaji Srinivasan.
Hazelcast has raised $86.5M across 5 funding rounds. Most recently, it raised $29.0M Series D in February 2020.