Real time data platform Hazelcast announces updates
|Richard Harris in Programming Tuesday, November 1, 2022|
Hazelcast announced at KubeCon North America that they have alleviated the 'Wait-and-See' paradigm that limits real-time applications stream processing via SQL and zero-code connectors, and their ultra-fast storage engine now addresses gaps in real-time architectures.
Hazelcast, Inc. is unveiling new capabilities at KubeCon North America that enable enterprises to join multiple streams of live data and merge them with large volumes of stored data to provide historical context, all within a single data processing platform. In addition to simplifying the overall data architecture for enterprise applications, Hazelcast now offers zero-code connectors to accelerate how quickly an enterprise can realize the benefits of stream processing and real-time applications in their existing infrastructure.
As more executives face urgent pressure to create new revenue opportunities, improve customer satisfaction or mitigate risk, real-time applications become a strategic enabler to achieve those goals. To embark on the path to real-time, application architects cannot depend on a database-centric approach. Databases inherently suffer from a processing bottleneck because data must be written before being analyzed. The stream processing engine of the Hazelcast Platform performs upstream, in-flight computation and simultaneously merges the data with the historical context withheld in the built-in, scalable, low-latency data store. The improved design results in a marked advancement over the batch-related "wait-and-see" paradigm.
Real-time data platform Hazelcast announces updates that alleviate the 'Wait-and-See' paradigm limiting real-time applications
"Hazelcast’s innovation of combining stream processing and low-latency data management into a single platform enables new opportunities for instant responsiveness, while also offering simplified management and operations in a real-time architecture. Thriving in the real-time economy requires instantaneous computation on both new and historical data, something traditional databases cannot do. After years of building our extremely reliable, low-latency data store, we’re focusing on the convergence with real-time data to give enterprises a new approach to improving customer satisfaction, generating new revenue, and mitigating risk," said Kelly Herrell, CEO of Hazelcast.
With the added stream-to-stream join functionality, enterprises can merge multiple data streams and handle late-arriving records. For example, an online business application may monitor both streams of orders and shipments to confirm accurate fulfillment, a success metric that keeps customers and users satisfied and loyal. By combining multiple streams with an ultra-fast, low-latency data store, enterprises can analyze and take action on the data without waiting for it to be written to a traditional database. This innovation is a significant competitive advantage for enterprises where time is of the essence.
"With time becoming the key competitive advantage for most businesses, the days of batch processing are dwindling. The Hazelcast Platform 5.2 release is yet another step towards helping our customers move to creating real-time actionable insights and delivering new digital experiences," said Manish Devgan, chief product officer of Hazelcast.
Simplified Data Integration via Zero-Code Connectors
Data unable to be queried for context enrichment of real-time insights is a lost opportunity. To ensure a user’s ability to take timely action on real-time insights, the Hazelcast Platform introduces zero-code connectors as a declarative method to retrieve contextual data from existing data platforms to simplify how application developers access and query data, as well as leverage pipelines. The Hazelcast zero-code connectors are in beta and currently support AWS Relational Database Services (RDS) for MySQL and PostgreSQL. Additional connectors will be available in upcoming releases.
Announced earlier this year, the Hazelcast Platform includes a Tiered Storage function that allows users to keep hot data in memory to increase throughput and reduce latency and maintain cold data in more cost-effective and operationally appropriate locations. The Tiered Storage capability is also highly performant, as its performance is on par with the Hazelcast Platform High-Density Memory Store feature. As an additional benefit, Tiered Storage enables users to enrich real-time data with reference data stored on NVMe-based SSDs.
Additional features in the latest release of Hazelcast Platform include:
- JSON SQL: Use standard JSON SQL functions for OBJECT and ARRAY aggregations
- Java Nested Objects: Users can now access and update fields of the complex type
- JDBC Driver: Use standard SQL tools like DBeaver to connect to Hazelcast
- Management Center SQL Browser: Improved usability of Management Center to execute streaming SQL
- Compact Serialization Generally Available (GA): Ready for production environments, Serialization now consumes less space, does not need editing, and enables seamless data model evolution
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