Hazelcast Extends the In-Memory Digital Integration Hub to the Cloud
Streaming SQL support added to enable end-to-end, standards-based data access
Hazelcast, the fast , released an update to its stream processing engine, Hazelcast Jet, that simplifies the migration to hybrid cloud environments by adding an Amazon Kinesis connector for out-of-the-box integrations with the leading messaging bus on Amazon Web Services (AWS). These additions to the streaming engine also standardize access methods to cloud storage via SQL, which enables enterprises to more easily build low-latency applications and leverage a fast access and query layer driven by a fast, in-memory digital integration hub (DIH) powered by Hazelcast.
The addition of a DIH to existing infrastructure reduces the number of calls and ultimately the stress on legacy and back-end systems while enabling the integration of modern technologies that add more capabilities for an architectural modernization strategy. An emerging use case, a DIH integrates numerous data sources to provide developers with a common application programming interface (API) to a fast data layer that supports high-speed applications, accelerating development, with shorter time-to-market. With similarities to data lakes, a DIH is a familiar data architecture to IT professionals but acts as an operational and fast view of data from backend systems for deploying business applications.
Recommended AI News: Acquia Named a Leader in the Gartner 2021 Magic Quadrant for DXP
“Architects are increasingly seeking an application platform that can run high-performance business applications in the cloud,” said David Brimley, chief product officer (CPO) at Hazelcast. “As more move to a digital integration hub, operational apps will deliver even more analytical outputs, and lead to new, real-time insights. This is in stark contrast to batch processing, which cannot support day-to-day operational applications.”
To enable low-latency, transactional cloud applications, Hazelcast can act as a fast access and query layer integrating data from various sources that are either slow or unsuitable for online usage. Already available in Hazelcast IMDG, SQL support was extended to Jet, allowing users to preprocess, query and analyze streaming data for online applications with extremely low-latency, microsecond tolerances. Additionally, the extended SQL API provides customers with the ability to query Kafka and object stores such as Hadoop, Amazon S3, Google Cloud Storage, Azure Cloud Storage and others.
Recommended AI News: CI Security Launches Multi-Tiered Solution to Reduce the Risk of Ransomware Attacks
Where the Hazelcast SQL offering differs from competitors is in its real-time processing proficiency. In addition to traditional SQL capabilities, its integration with Hazelcast Jet allows enterprises to combine cached, Kafka and file-based data into a single query, as well as simply ingesting data, all without having to write any additional code.
While Hazelcast Jet is used to ingest and preprocess data, a highly performant data store is still required to analyze and act upon the insights. In deploying an integrated in-memory computing platform featuring Hazelcast Jet and Hazelcast IMDG, an end-to-end SQL data flow delivers low-latency for mission-critical applications. In this environment, IMDG acts as the data store by caching the data for fast consumption. This unique combination of capabilities in an integrated platform delivers architectural flexibility for modern applications and real-time customer insights.