Hazelcast Blog


Hazelcast Releases Cloud-based Architecture for Financial Services Risk Management Applications

Press Release – Feb 24, 2021

Hazelcast is releasing a reference implementation that simplifies a financial service organization’s ability to execute and scale financial risk calculations in the cloud while gaining real-time performance and fully-utilizing the resource-heavy investment.

Hazelcast Broadens Global Partner Program to Drive Cloud Adoption

Press Release – Feb 9, 2021

Hazelcast announced the expansion of its channel program to include several new partners that increase the company’s go-to-market capabilities in verticals and regions experiencing strong cloud adoption.

Hazelcast Jet 4.4 brings SQL to stream processing engine

Media Coverage – Feb 8, 2021

Hazelcast Jet brings new SQL query capabilities to the stream processing platform that will enable developers to continuously query streaming data without interrupting data flow.


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Banking: Making AI in Customer Service A Reality

Media Coverage – Oct 12, 2020

Hazelcast discusses how in-memory computing and AI are the key to up-selling at scale in the financial services sector.

Data firehose: Next generation of streaming technologies goes cloud-native

Media Coverage – Oct 9, 2020

Real-time streaming data has become a reality for an increasing number of enterprise applications.

Hazelcast to Provide Additional Capabilities to IBM Cloud Pak for Multicloud Management

Press Release – Oct 7, 2020

San Mateo, Calif., October 7, 2020 – Hazelcast, the leading open source in-memory computing platform, today announced that IBM will offer the Hazelcast In-Memory Computing Platform (IMCP) integrated as part of IBM’s Cloud Pak offerings, enterprise-ready containerized software running on Red Hat OpenShift. IBM’s Cloud Paks, including the Cloud Pak for Multicloud Management, can now […]

Hazelcast Adds SQL Support in Latest Upgrade

Media Coverage – Sep 17, 2020

In-memory computing platform maker has Hazelcast is adding new features and enhancements to its namesake Java-based in-memory data grid.

Stream Processing Is a Great Addition to Data Grid, Hazelcast Finds

Media Coverage – Sep 14, 2020

In-memory data grids (IMDGs) historically have exceled in applications that require the fastest processing times and the lowest latencies. By adding a stream processing engine, called Jet, to its IMDG, Hazelcast is finding customers exploring new use cases at the cutting edge of high-performance computing.

Achieving‌ ‌Low‌ ‌Latency‌ ‌in‌ ‌the‌ ‌Public‌ ‌Cloud‌

Media Coverage – Sep 14, 2020

As all online business becomes more competitive – within the same industry and in the broader realm of customer experience in web and mobile apps – low latency will continue to be a priority. So as a business, how can you ensure the highest performance from your systems when moving to the cloud?

John DesJardins on In-Memory Data Grids, Stream Processing, and App Modernization

Media Coverage – Sep 14, 2020

In this podcast, John DesJardins, field CTO and VP solution architecture at Hazelcast, sat down with InfoQ podcast co-host Daniel Bryant. Topics discussed included: how in-memory data grids have evolved, use cases at the edge (IoT, ML inference), integration of stream processing APIs and techniques, and how data grids can be used within application modernization.

Using Edge Technology to Achieve Near Real-Time Insights

Media Coverage – Sep 11, 2020

Edge computing has enormous potential to transform how companies leverage data to produce value.

Hazelcast Advances Leadership, Lowers Barrier of Adoption to In-Memory Digital Integration Hubs

Press Release – Sep 9, 2020

Hazelcast today announced a new major feature and a number of enhancements to its in-memory data grid (IMDG), Hazelcast IMDG.