Hazelcast Unified Real-Time Data Platform
Build applications that act instantly on streaming data
The Hazelcast platform is a powerful blend of a stream processing engine and a fast data store. It's designed to handle real-time streaming data, analyze it alongside historical information, and help businesses take action instantly.
Simply said, our platform’s unique unified architecture reduces the number of separate software components in your architecture to speed up the development and deployment of applications.
Hazelcast Unified Real-Time Data Platform
With Hazelcast, you can harness the full potential of real-time data without the complexity of integrating multiple software components. Our unified platform handles growth demands, unexpected load spikes, hardware failures of multitudes of components, downtime, and ongoing administrative tasks. What’s more, it integrates with your existing infrastructure, so there’s no need to rip and replace technology to give your applications the ability to act instantly on data in motion.
Automate data architectures for instant action
Seamlessly deploy machine learning models with real-time data for fast, efficient predictions, and optimal performance in AI, event-driven, and edge use cases.
Streamline data architectures for efficiency, speed, and ROI
Hazelcast Platform’s compact hardware footprint handles growing workloads effortlessly, while providing ultra-fast performance and cost-effective usage.
Enhance data architectures for future-proof growth
Hazelcast Platform supports various use cases, ensuring high availability with low RPO and RTO for disaster recovery. It minimizes planned downtime and supports zero downtime and zero data loss during application upgrades.
Hazelcast Platform Features
The core engine for processing your data in motion
Hazelcast Platform enables event stream processing and fast batch processing at any scale. It retrieves live data from databases, data lakes, applications, devices, and message brokers like Apache Kafka, Apache Pulsar, AWS Kinesis, or RabbitMQ. It then transforms raw, high-volume data streams into business events and actionable insights, making them easily consumable by applications, dashboards, and databases.
The multi-purpose engine for your real-time deployments
Hazelcast connects a set of networked/clustered compute resources to let applications share data structures and run parallelized workloads in the cluster.
The primary advantage is speed, which has become critical in an environment with billions of mobile, IoT devices and other sources continuously streaming data. With all relevant information in RAM, there is no need to traverse a network to remote storage for transaction processing. The difference in speed is significant – minutes vs. sub-millisecond response times for complex transactions done millions of times per second.
Out-of-the-box connectivity to your existing data platforms
The platform empowers you to effortlessly integrate diverse applications and data systems, eliminating the need for additional code. Take your data architecture to the next level with our extensive range of pre-built connectors, including support for all connectors in the Kafka Connect ecosystem, enabling swift modernization and powerful integrations at any scale.
Leverage SQL for both data in motion and data at rest
SQL support provides a familiar interface for running queries and offers the following benefits:
Industry-standard querying: Query large volumes of data using an industry-standard approach, maintaining the same query specificity as the existing Hazelcast Predicate-based design.
High-performance indexing: Take advantage of new, high-performance concurrent off-heap B+ tree indexes to optimize query performance.
Advanced query optimization: Benefit from advanced query optimization techniques to enhance the efficiency of your queries.
Manage and monitor your Hazelcast deployments
During development, Management Center provides deep insights. In production, it can be used by IT operations or integrated with enterprise monitoring tools via REST and JMX. With a commercial license from Hazelcast, you can use Management Center to monitor a cluster of any size.
Protect your data with role-based access controls and encryption
Hazelcast ensures industry-leading security with end-to-end TLS encryption, mutual authentication using X509 certificates, and roles-based authorization via the standard Java Authentication and Authorization Service (JAAS). It seamlessly integrates security into your application, streamlining the protection of sensitive data. By combining industry security standards and user-friendly APIs, it maintains optimal performance while providing peace of mind.
Ready to level up your applications with lightning-fast, real-time stream processing?
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- Automated Instant Action
- Streamlined Efficiency and Speed
- Enhanced Future-Proof Growth
A unified real-time data platform combines critical components of a real-time system into a single, tightly integrated cluster. Hazelcast satisfies these requirements by offering a high-performance stream processing engine and an ultra-fast data store within the same cluster. With fewer moving parts to manage, Hazelcast provides state storage, resilience through snapshots, fast stream enrichment lookups, and digital integration hub capabilities, all essential for real-time stream processing deployments.
Hazelcast is used over other streaming data platforms for 3 key reasons:
It is designed for instant action, where your applications can automate work so you can take advantage of time-sensitive opportunities that are otherwise buried in the data.
It simplifies application development and deployment by reducing the number of siloed technologies that add complexity to a streaming data deployment.
It has proven superior performance (check out our results in the ESPBench benchmark from the Hasso Plattner Institute and the NEXMark benchmark).
Stream processing refers to the advanced analysis and manipulation of data streams in real-time. It involves performing tasks such as stateful aggregations, window operations, mutations, and materialized view creation on an endless flow of data.
Event streaming provides the infrastructure and means to transmit and store real-time data streams. Stream processing, on the other hand, is the next step that involves processing and analyzing these data streams for more meaningful insights and actions.
The main difference lies in their primary purposes and functionalities. Event streaming deals with the transportation and persistence of data streams, while stream processing focuses on the real-time analysis and transformation of those streams.
Absolutely! Event streaming platforms like Apache Kafka serve as a reliable foundation for transmitting and storing data streams, while stream processing technologies like Apache Flink and Spark Streaming and Hazelcast platform allow developers to process and derive valuable insights from these streams.
Stream processing enables real-time data analysis, providing immediate insights and faster responses to dynamic data changes. In contrast, traditional batch processing processes data in fixed intervals, resulting in delayed insights and actions.
Hazelcast platform excels in stream processing by offering developers an optimized approach to handle real-time data streams. It leverages the powerful aggregation framework to efficiently process streams and unlock their full potential, enabling businesses to make well-informed and prompt decisions.