SAN MATEO, Calif., July 14, 2020 /PRNewswire/ -- Hazelcast, the leading open source in-memory computing platform, today announced the latest release of Hazelcast Jet which includes new application development features to its stream processing architecture. This new release enables existing infrastructure to gracefully extend to an event-driven architecture, enabling new functionality with real-time and in-memory processing.
According to a survey of IT decision makers, companies realized business value when employing stream processing to support the customer experience (44%), better risk management (42%), increased real-time analytics (40%) and improved fraud detection and prevention (39%). However, many of today's streaming solutions require additional bolt-on systems that increase latency, require additional skillsets and complicated integrations with legacy and emerging technologies. With Hazelcast Jet, enterprises receive a portable event-driven platform in a lightweight package that is capable of being deployed on-premises, in the cloud and at the edge.
"From its real-time performance to its lightweight, simplified architecture, Jet is an ideal technology foundation for application modernization," said David Brimley, chief product officer (CPO) at Hazelcast. "As enterprises are seeking to extend the life of legacy investments, the latest update to Hazelcast Jet equips customers to take advantage of more data sources and execute additional processing, all the while achieving greater efficiencies from their hardware investments."
Application Modernization with an Event-Driven Architecture
Overhauling applications with monolithic architectures can be a daunting and costly task, but there are steps an enterprise can take to begin the transition to a microservices architecture that provides future flexibility. To reduce the effort required by developers, Hazelcast Jet now supports streaming integration with MySQL and PostgreSQL databases using a unified high-level API. Previously, traditional RDBMS-based applications required hundreds or thousands of lines of code to add functionality to existing applications and significant testing effort. With the new API, the integration becomes more of a declarative task to reduce the custom error-prone code.
Additionally, Hazelcast Jet makes the database available as a stream. It deals with connectivity, object mapping and unifies the event handling across database vendors. The series of database updates form an event stream on which developers can more easily add microservices without impacting existing applications. This simplification lets developers focus on adding new business logic in high-performance applications rather than managing complex and error-prone integrations.
The transactional data from MySQL or PostgreSQL can be augmented and enriched with other datasets from Hadoop, Amazon S3, Google Cloud Storage, Azure Data Lake and more and served through thousands of concurrent low-latency queries as well as fine-grained, key-based access. It's a quick method of improving the customer experience by providing fresh analytical insights in user-facing applications
With these enhancements, enterprises can take advantage of in-memory speeds to accelerate analytical queries to scale your architecture by offloading certain workloads from your transactional database into an in-memory store. Example use cases include back-office trade monitoring, on-demand parameterized recommendations and real-time, in-memory materialized views.
New Connectors and Optimizations
Earlier this year, change data capture (CDC) via the Debezium open source project was integrated into Hazelcast Jet. In the current release, the CDC integration has been optimized to reduce the manual coding necessary to utilize this capability.
Over the last year, the library of connectors for Hazelcast Jet has expanded to include Apache Beam, Confluent, MongoDB, JDBC, Apache Cassandra® and others. The latest release now includes connectors for Elasticsearch and Apache Pulsar. In connecting Hazelcast Jet to Elasticsearch, enterprises can rapidly enrich large data sets, including those from relational databases, and transform them into formats suitable for indexing and search-based analysis by Elasticsearch.
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.