Hazelcast Jet is a lightweight, scalable, real-time streaming engine for
continuous intelligence applications
PALO ALTO, Calif.–(BUSINESS WIRE)–lt;a href=”https://twitter.com/hashtag/IoT?src=hash” target=”_blank”gt;#IoTlt;/agt;–Hazelcast,
the leading in-memory computing platform company, today announced the
general availability of Hazelcast Jet, the only streaming engine with no
external system dependencies. The result is the industry’s fastest
stream processing engine that dramatically simplifies implementation
from the smallest to largest deployments.
Whether deployed in constrained environments, such as IoT sensors, or
cloud-scale applications, Hazelcast Jet ingests, categorizes and
processes vast amounts of data with ultra-low latency to support
continuous intelligence practices.
“SigmaStream specializes in high-frequency data and works with some of
the world’s largest companies that operate in the most constrained
environments. By integrating Hazelcast Jet’s high-performance streaming
engine with our Hummingbird visualization and processing platform, we
process high-frequency data from dozens of channels and address
inefficiencies in real-time,” said Hari Koduru, CEO of SigmaStream. “The
performance and optimization at such a fine level enable SigmaStream’s
customers to shrink the time spent on a project, ultimately saving them
millions of dollars.”
Single System Design
Normally, deploying other streaming engines requires enterprises to
invest the time and endure the complexity of integrating multiple
components from different sources. For example, a Flink implementation
would necessitate integrating a combination of Kafka, ZooKeeper,
RocksDB, Hadoop File System and resource managers to ingest, categorize
and process data.
Hazelcast Jet significantly simplifies deployment because it is a
single, lightweight system that elegantly addresses a complex set of
architectural requirements. Hazelcast Jet’s unique single-system design
enables rapid time-to-value, eliminates costs and complexity associated
with multi-component architectures, and reduces the need for multiple
Industry’s Fastest Streaming
Internal benchmarks demonstrate Hazelcast Jet’s ability to maintain
millisecond speeds at extreme scale, where other open source-based
projects drop into the seconds. Hazelcast Jet maintains its ultra-low
latency, regardless of scale, due to a distributed architecture and
“Hazelcast has once again delivered a powerful leap forward for the
industry, this time by radically simplifying how stream event processing
is implemented,” said Kelly Herrell, CEO of Hazelcast. “Time is money,
and the ability to process data at the moment it is generated — wherever
it is generated — produces measurable business benefits whether at a
financial trading desk or edge-based sensors. When time matters,
companies choose Hazelcast and now they have a compelling and flexible
streaming solution for fast data processing in Hazelcast Jet.”
Importantly, Hazelcast Jet delivers low-latency performance regardless
of scale, whether running at the IoT edge in small-format hardware or as
a massive cluster in data centers and clouds.
Hazelcast Jet’s architecture is simultaneously lightweight and highly
scalable, allowing it to run wherever customers need high-performance
stream processing. Its small file size and architecture provide numerous
deployment options, including in Kubernetes microservices environments,
private data centers, public clouds or embedded in applications.
Furthering the deployment simplicity of Hazelcast Jet, it is
Kubernetes-ready to support containerized workloads and validated to run
in Pivotal Cloud Foundry and Red Hat OpenShift cloud environments.
Elastic and Resilient
As workloads increase, Hazelcast Jet’s clustering model scales up and
down without job interruption.
Hazelcast Jet clusters can be taken offline without losing data and jobs
can be upgraded without interrupting processing, a significant benefit
for long-running continuous streaming applications. In the event of an
outage, in-memory data replication provides a robust yet performant
means of fault tolerance, with Hot Restart for fast recovery. The
in-memory data can also be continuously persisted to disk for
maintenance shutdowns or lights-out events.
Machine Learning Modeling
Whereas most streaming engines use batch processing to manage data,
Hazelcast Jet is capable of processing the event upon ingestion. With
real-time processing, Hazelcast Jet is a reliable solution for serving
machine learning models that require the latest information to inform
Furthermore, Hazelcast Jet integrates with TensorFlow to run real-time
classification and prediction workloads at scale. Customers can choose
whether they want to use the embedded, in-process Java runner or a
remote TensorFlow Serving option.
In-Memory Computing Platform
Combining Hazelcast Jet with Hazelcast IMDG enables enterprises to
deploy a high-performance and scalable in-memory computing platform that
handles data in motion and at rest.
Hazelcast uniquely presents customers with the ability to utilize a
common architecture and skill sets to ingest and process streaming data,
while also providing storage and computation of data, all at
industry-leading low latency.
Availability and Resources
Hazelcast Jet 3.0 is available
today for download.
For more information on Hazelcast Jet 3.0, please visit these additional
About Hazelcast, Inc.
Headquartered in Silicon Valley, Hazelcast is the leading in-memory
computing platform company which addresses the growing demand for
enhanced application performance, data processing speed and scalability.
Hazelcast’s in-memory computing platform is comprised of two core
products: Hazelcast IMDG and Jet. Hazelcast IMDG is an in-memory data
grid proven to provide the performance at scale required by the world’s
largest organizations. Hazelcast Jet is an ultra-fast, application
embeddable, stream and batch processing engine capable of supporting
real-time streaming data. The company also offers Hazelcast Cloud, a
fully managed, low latency data layer for cloud-based workloads at any
Hazelcast’s customers include six of the world’s 10 largest banks and 36
of the Fortune Global 500; its technology is deployed at nearly every
major credit card company, five of the world’s largest e-commerce
companies and four of the largest telecommunications companies.
Director of Communications,