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Hazelcast Overview

Hazelcast is a distributed computation and storage platform for consistently low-latency querying, aggregation and stateful computation against event streams and traditional data sources. It allows you to quickly build resource-efficient, real-time applications. You can deploy it at any scale from small edge devices to a large cluster of cloud instances.

Hazelcast can process data on a set of networked and clustered computers that pool together their random access memories (RAM) to let applications share data with other applications running in the cluster. When data is stored in RAM, applications run a lot faster since it does not need to be retrieved from disk and put into RAM prior to processing. Using Hazelcast, you can store and process your data in RAM, spread and replicate it across a cluster of machines; replication gives you resilience to failures of cluster members.

Hazelcast is implemented in Java language and has clients for Java, C++, .NET, REST, Python, Go and Node.js. Hazelcast also speaks Memcached and REST protocols.

Your cloud-native applications can easily use Hazelcast. It is flexible enough to use as a data and computing platform out-of-the-box or as a framework for your own cloud-native applications and microservices.

Hazelcast is designed to be lightweight and easy to use. Since it is delivered as a compact library, it easily plugs into your software solution.

It is designed to scale up to hundreds of members and thousands of clients. When you add new members, they automatically discover the cluster and linearly increase both the memory and processing capacity. The members maintain a TCP connection between each other and all communication is performed through this layer. Each cluster member is configured to be the same in terms of functionality. The oldest member (the first member created in the cluster) automatically performs the stored and streaming data assignment to cluster members. If the oldest member dies, the second oldest member takes over.

Hazelcast offers simple scalability, partitioning (sharding), and re-balancing out-of-the-box. It does not require any extra coordination processes. NoSQL and traditional databases are difficult to scale out and manage. They require additional processes for coordination and high availability. With Hazelcast, when you start another process to add more capacity, data and backups are automatically and evenly balanced.

What Can You Do with Hazelcast?

You can request data, listen to events, submit data processing tasks using Hazelcast clients connected to a cluster. Hazelcast has clients implemented in Java, .Net, C++, Node.js, Go and Python languages. It also communicates with Memcache and REST protocols. See the Hazelcast Clients section.

You can build data pipelines using SQL or the Java API which enable the data to flow from an application to a data source or from a data source to an analytics database. A very simple example can be reading words from a file, converting them into all-uppercase, and output the results to your console. See the Building Data Pipelines section.

You can import data from databases, files, messaging systems, on-premise and cloud systems in various formats (data ingestion). Hazelcast offers pipelines and loading/storing interfaces for this purpose. See the Ingesting Data section.

You can run queries on the data using SQL in your maps or external systems like Apache Kafka. You can also use the predicates API to filter and retrieve data in your maps. See the Distributed Queries section.

You can run computational tasks on different cluster members (distributed computing); for this you can use the pipelines, entry processors, and executor services. See Distributed Computing section.

You can store your data using the distributed implementation of various data structures like maps, caches, queues, topics, concurrency utilities. See the Distributed Data Structures section.

You can use it as a distributed second level cache for your Hibernate entities, collections and queries. Also, Hazelcast can be used as a cache for applications based on the Spring Framework for distributing shared data in real time.

You can have multiple Hazelcast clusters at different locations in sync by replicating their state over WAN environments. See the Synchronizing Data Across a WAN section.

You can listen to the events happening in the cluster, on the data structures and clients so that you are notified when those events happen. See the Distributed Events section.

Please see the Develop Solutions chapter for all the scenarios you can realize using Hazelcast.

The following are example use cases:

  • Increasing the transactions per second and system uptime in payment processing

  • Authorizing and authenticating the credit cards using multiple algorithms within milliseconds for fraud detection

  • Decreasing order processing times with low latencies in e-commerce

  • Being a real-time streamer to detect application performance

  • Clustering highly changing data with event notifications, e.g., user based events, and queueing and distributing background tasks

  • Being a distributed topic (publish/subscribe server) to build scalable chat servers for smartphones

  • Constructing a strongly consistent layer using its CP (CP with respect the CAP principle) subsystem built on top of the Raft consensus algorithm

  • Distributing user object states across the cluster, to pass messages between objects and to share system data structures (static initialization state, mirrored objects, object identity generators)

  • Being a multi-tenancy cache where each tenant has its own stored data

  • Sharing datasets, e.g., table-like data structure, to be used by applications

  • Storing session data in web applications (enabling horizontal scalability of the web application)

The applications call for stored data from data sources, e.g., databases, and these sources are slow since they are not designed to respond in time. Hazelcast runs in the shared standard memories (RAMs) of a cluster of servers which sits in between the applications and the datasources. It gets data from the data sources, pulls it up in the memory and serves it to the applications at in-memory speeds, instead of RPM speeds. This makes Hazelcast a low-latency solution (fast response times).

When it comes to streaming data, they come from sources like files, Apache Kafka, IoT and MQ and they are born in the moment. Hazelcast captures this data in the moment and effectively processes it on the wire. And this makes Hazelcast a real-time processing platform.

The unique capability of Hazelcast is its ability to process both batch and streaming data, with low latency and in real-time, enabling transactional and analytical processing.

Hazelcast Editions and Features

Hazelcast has Open Source and Enterprise editions. Hazelcast Enterprise is the licensed commercial offering built on top of the Open Source product.

The Open Source edition of Hazelcast offers the following features:

  • Distributed computation, data structures, and events

  • Streaming data processing

  • Connectors to read from/write to systems like Apache Kafka, JMS, JDBC and HDMS

  • Querying with SQL and predicates

  • CP subsystem for distributed coordination use cases

  • JCache implementation

  • Replication of web sessions (filter, Tomcat, Jetty based)

  • Administration and monitoring utilities including Management Center, JMX, metrics and diagnostics

The Enterprise edition of Hazelcast offers the following features in addition to the ones listed above:

  • High-Density Memory Store (off-heap memory)

  • Persistence

  • Lossless cluster restarts

  • Rolling upgrades

  • Job upgrades

  • Unlimited members on Hazelcast Management Center (it is restricted to 3 members on the freely available version of Management Center)

  • CP Subsystem Persistence

  • Security Suite (RBAC, TLS, Mutual Auth, Client Certificates)

  • WAN Replication (syncing data between two geo-replicated clusters)

  • Blue/Green Deployments

All preexisting Hazelcast licenses (former Pro/Enterprise/Enterprise HD licenses) work with Hazelcast 5.0.

Licenses and Support

Hazelcast Open Source edition is free and covered by Apache License, Version 2.0 and Hazelcast Community License. Permissions are granted to use, reproduce and distribute it along with any kind of open source and closed source applications.

Hazelcast Enterprise edition is a commercial product of Hazelcast, Inc. and distributed under a commercial license that must be acquired before using it in any type of released software. Feel free to contact Hazelcast sales department for more information on commercial offers.

Hazelcast provides two types of support: community and customer.

Community Support

Community support is for every Hazelcast user. You can use the following channels for this purpose:

Customer Support

Customer support is for paying Hazelcast customers. See hazelcast.com for the support options. A support subscription from Hazelcast will allow you to get the most value out of your selection of Hazelcast. Our customers benefit from rapid response times to technical support inquiries, access to critical software patches, and other services which will help you achieve increased productivity and quality. Learn more about Hazelcast support subscriptions: https://hazelcast.com/pricing/

If your organization subscribes to Hazelcast Support, and you already have an account setup, you can login to your account and open a support request using our ticketing system: https://hazelcast.zendesk.com/.

When submitting a ticket to Hazelcast, please provide as much information and data as possible:

  • Make sure that all your environments are capturing Hazelcast diagnostics logs. This a primary on diagnosing issues with Hazelcast environments.

  • If your environments are not capturing diagnostics logs, please update them to capture diagnostics logs.

  • Make note of your issue with a clear description of the issue for a title text. This will allow Support to route the issue to the proper expert

  • Make a note of the steps to reproduce if possible. If not please capture the sequence of events that led to the problem.

  • Write a complete description of the problem along with any error found.

  • Capture any relevant screen shots and or errors noted.

  • Create a support ticket on Hazelcast Zendesk support Portal.

  • Attach the appropriate severity to the ticket.

  • PROD issues that affect production are considered as severity 1.

  • All other issues in other environments are considered severity 2 or 3 depending on urgency.

  • DEV issues are considered as severity 3 and priority low.

  • All other issues, e.g., questions or documentation review are considered as severity 3 or higher.

Adding Details to the Support Ticket

  • When you open a support ticket add a concise title and description of the problem.

  • Add steps to reproduce as best as you can document them so that support can attempt to reproduce the problem. This includes Detailed description of incident – what happened and when.

  • Add a reproducible test case, this is optional - Hazelcast engineering may ask for it if required.

  • Add details of use case. This is crucial as it helps support narrow down the features and functionality in play when the problem occurred.

  • Attach any specific errors found.

  • Attach the complete logs files, i.e., Hazelcast logs.

  • Attach Hazelcast process logs.

  • Attach Hazelcast health monitor logs.

  • Attach thread dumps from all members.

  • Attach heap dumps.

  • Add networking logs.

  • Specify the time of incident.

  • When providing Hazelcast logs, please make sure that the system and environment details that are captured at system startup are included, even if you truncate the logs.

  • Add Hazelcast diagnostic logs. Please do not truncate diagnostics logs. They only capture Hazelcast systems specific information and details.

  • Please make sure that the logs capture data around the date and time of the incident.

Please consider the above for prompt help from support and note that the more information is provided upfront the better. Lastly be prompt in your communication with Hazelcast support - helps to ensure timely resolution of issues.

Architecture Overview

The fundamental key components of Hazelcast are as follows:

  • A member is the computational and data storage unit in Hazelcast. Typically it is a JVM.

  • A Hazelcast cluster is a set of members communicating with each other. Members which run Hazelcast automatically discover one another and form a cluster at runtime.

  • Partitions are the memory segments that store portions of data. They are distributed evenly among the available cluster members. They can contain hundreds or thousands of data entries each, depending on the memory capacity of your system. Hazelcast also automatically creates backups of these partitions which are also distributed in the cluster. This makes Hazelcast resilient to data loss.

Hazelcast’s streaming engine focuses on data transformation while it does all the heavy lifting of getting the data flowing and computation running across a cluster of members. It supports working with both bounded (batch) and unbounded (streaming) data.

Hazelcast’s storage engine is the distributed, fast, and operational data store dealing with persistence of data.

Hazelcast comes out of the box with different sources and sinks. Sources are where Hazelcast pulls the data, and sinks are where it outputs the processed data result. Sources and sinks are also referred to as connectors. Its unified connector API provides a simple way to read files, unified across different sources of the data. See the Sources and Sinks section for more information on the unified connector API and the supported sources and sinks.