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

Latest version of Hazelcast IMDG adds SQL support, improves reliability, simplifies cluster discovery in the cloud and more SAN MATEO, Calif., Sept. 9, 2020 /PRNewswire/ — Hazelcast, the leading open source in-memory computing platform, today announced a new major feature and a number of enhancements to its in-memory data grid […]

Latest version of Hazelcast IMDG adds SQL support, improves reliability, simplifies cluster discovery in the cloud and more

SAN MATEO, Calif., Sept. 9, 2020 /PRNewswire/ — Hazelcast, the leading open source in-memory computing platform, today announced a new major feature and a number of enhancements to its in-memory data grid (IMDG), Hazelcast IMDG. Among the updates are preview support for managing distributed data using SQL, out-of-the-box support for Kerberos, additional tuning options for Intel® Optane™ DC Persistent Memory Modules and quicker cluster rebalancing. With the latest version of Hazelcast IMDG, use cases such as digital integration hubs gain improved performance, scalability and resiliency.

Hazelcast Logo (PRNewsfoto/Hazelcast, Inc.)
Hazelcast Logo (PRNewsfoto/Hazelcast, Inc.)

The combination of business leaders requiring tailored views of data and the proliferation of data sources is stressing legacy architectures and infrastructure. An emerging answer to these challenges is a new architecture, digital integration hubs, that is a data architecture that provides a single access point and standardized API that can be called upon by multiple applications. These hubs are often deployed to reduce workloads on backend systems, to accelerate access to data hosted in backend databases and mainframes, and to provide a common API to a variety of data sources  to integrate new technologies into legacy architectures. Hazelcast empowers proven, in-memory digital integration hubs by providing object storage in RAM, write-through caching, distributed processing and predefined connectors to many popular data sources.

“Evolving legacy architectures, especially those with heterogeneous backends, toward new data channels pose a technological challenge of how to put all the pieces together while keeping the overall complexity maintainable. Digital integration hubs provide a central access point to those backend data sources that multiple applications can call upon uniformly,” said Kelly Herrell, CEO of Hazelcast. “Given that the hubs are the central component of these architectures, it needs to be fast, scalable, reliable and secure. The Hazelcast In-Memory Computing Platform provides the necessary capabilities that not only fulfill the requirements of the largest enterprises, but significantly simplifies the deployment and operational experiences when working with these innovative new digital integration hub architectures.”

Introducing SQL Support
To complement the existing APIs for languages including Java, .NET, Node.js, Python, C++ and Go, Hazelcast IMDG is introducing SQL support. Adding this capability to Hazelcast IMDG enables digital integration hubs to retrieve data using a common well-known API. Usage of indexes to speed up the queries, along with the ability to filter results on attributes extends Hazelcast IMDG beyond the limited query-by-key capability of basic key-value stores. The familiarity equates to simplified development and reduced implementation costs as well.

“Given its widespread familiarity among developers, the addition of SQL support significantly reduces the learning curve and opens up new opportunities for enterprises to tap into the benefits of an in-memory computing platform,” said David Brimley, chief product officer at Hazelcast. “With SQL, it’s even more straightforward to let Hazelcast IMDG do the heavy lifting of retrieving data from multiple nodes, in parallel and ensuring correctness without introducing extra development costs.”

In this release, the SQL support is intended for “select” queries on Hazelcast IMDG maps already populated with data. Additional capabilities, such as joins, aggregations and sorting will be added in future releases.

Accelerated Cluster Rebalancing and Improved Network Failure Detection
Since a digital integration hub is the primary access point for business-critical applications, any downtime can carry significant penalties, including potentially lost revenue and/or customers. Should a hardware failure occur, such as a computer crash, the cluster must restore the lost data immediately by promoting the backups of the lost partitions. However, the restoration process still requires the rebalancing of partitions across the cluster. In this release, Hazelcast is introducing parallel partition migrations which accelerates cluster rebalancing and reduces the time spent in a suboptimal state by an order of magnitude. As an example, should a network disconnect one node in a 10-node cluster responsible for storing four terabytes of data, Hazelcast IMDG will be able to complete partition rebalancing in approximately 2 minutes when it would have previously required at least 33 minutes.

To further reduce the possibility of downtime, Hazelcast IMDG improves its partial network failure detection capabilities utilizing the implementation of the Bron–Kerbosch algorithm. This enhancement translates to improved high-availability in scenarios where a Hazelcast IMDG cluster must recover from hard-to-detect network failure scenarios.

Out-of-the-Box Kerberos Authentication
Hazelcast is introducing first-class, out-of-the-box support for Kerberos, a widely used authentication protocol. By integrating Kerberos support into Hazelcast IMDG, the engineering time and risks associated with manual integration are greatly reduced. The Kerberos protocol complements the enterprise-grade security suite of Hazelcast IMDG Enterprise.

Cost-Efficient Data, Cloud-Friendly Updates and More
Through the on-going co-engineering activities with Intel, Hazelcast continues to optimize its platform to take full advantage of Intel Optane DC Persistent Memory Modules. This release features the ability to use all Intel Optane Persistent Memory Modules installed in a system resulting in the ability for enterprises to build cost-efficient, terabyte-sized in-memory deployments. In addition, Hazelcast added performance tuning options that can increase the throughput of the system by 50% to gain near RAM-like speeds for half the cost in select use cases.

The latest release enables even easier ways to incorporate Hazelcast IMDG into existing architectures as part of application modernization initiatives. In particular, Hazelcast IMDG is now able to:

  • Form a cluster in the cloud with a single line of configuration, which shrinks the setup time to seconds

  • Adjust the configuration without touching configuration files to reduce the DevOps overhead of distributed setups like with Kubernetes

Hazelcast IMDG 4.1 beta is available today and general availability (GA) is expected later this year.

Additional Resources

About Hazelcast, Inc.
Hazelcast delivers the in-memory computing platform that empowers Global 2000 enterprises to achieve ultra-fast application performance – at any scale. Built for low-latency data processing, Hazelcast’s cloud-native in-memory data store and event stream processing software technologies are trusted by leading companies such as JPMorgan Chase, Charter Communications, Ellie Mae and National Australia Bank to accelerate data-centric applications.

Hazelcast is headquartered in San Mateo, CA, with offices across the globe. To learn more about Hazelcast, visit https://hazelcast.com.


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SOURCE Hazelcast, Inc.

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