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Description

The HiveMQ Platform provides a scalable, reliable data backbone with an event-driven MQTT architecture. Here are a few highlights: 1. MQTT Broker: At the heart of the HiveMQ platform is a fully MQTT-compliant broker purpose-built for fast, reliable, bi-directional data movement between IoT devices and enterprise systems. 2. Edge Data Integration: HiveMQ Edge seamlessly integrates edge data by converting industrial protocols into standardized MQTT, enabling an interoperable IIoT infrastructure. 3. IoT Streaming Governance: Data Hub transforms data in flight, passing only the most relevant, contextualized data to cloud and enterprise systems. 4. UNS & IT/OT convergence Enabler: Commonly used as the backbone for Unified Namespace architectures and seamlessly connects OT devices with IT systems for full visibility and interoperability. 5. Distributed Data Intelligence: HiveMQ Pulse unifies and contextualizes data across the enterprise for smarter decisions exactly where they matter most. 6. Maximum Interoperability: Runs anywhere on-premises or in public or private clouds. Efficiently connects to streaming applications, databases and data lakes with a Java SDK to build your own 7. Scalability to Support Growth: Elastic scaling with automatic data balancing and smart message distribution. Proven benchmark of up to 200M active clients with 1.8B messages/hour 8. Business Critical Reliability: Zero message loss with persistence to disk and offline queuing. No single point of failure due to masterless cluster architecture and zero downtime upgrades

Description

IBM Event Streams is a comprehensive event streaming service based on Apache Kafka, aimed at assisting businesses in managing and reacting to real-time data flows. It offers features such as machine learning integration, high availability, and secure deployment in the cloud, empowering organizations to develop smart applications that respond to events in real time. The platform is designed to accommodate multi-cloud infrastructures, disaster recovery options, and geo-replication, making it particularly suitable for critical operational tasks. By facilitating the construction and scaling of real-time, event-driven solutions, IBM Event Streams ensures that data is processed with speed and efficiency, ultimately enhancing business agility and responsiveness. As a result, organizations can harness the power of real-time data to drive innovation and improve decision-making processes.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Apache Kafka
Amazon Kinesis
Amazon Web Services (AWS)
Cogent DataHub
Docker
Google Cloud Pub/Sub
IBM MQ on Cloud
InfluxDB
Kubernetes
Microsoft Azure
MongoDB Atlas
MySQL
Snowflake
Waterstream
meshIQ

Integrations

Apache Kafka
Amazon Kinesis
Amazon Web Services (AWS)
Cogent DataHub
Docker
Google Cloud Pub/Sub
IBM MQ on Cloud
InfluxDB
Kubernetes
Microsoft Azure
MongoDB Atlas
MySQL
Snowflake
Waterstream
meshIQ

Pricing Details

$0.34/hour
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

HiveMQ

Founded

2012

Country

Germany

Website

www.hivemq.com

Vendor Details

Company Name

IBM

Founded

1911

Country

United States

Website

www.ibm.com/products/event-streams

Product Features

Industrial IoT

Condition Monitoring
Data Visualization
Factory Data Analytics
Machine Learning
Machine Workflow Creation
Predictive Maintenance
Production Line / Factory Insights
Real-Time Monitoring
Reporting / Analytics
Smart Alerts / Notifications

IoT

Application Development
Big Data Analytics
Configuration Management
Connectivity Management
Data Collection
Data Management
Device Management
Performance Management
Prototyping
Visualization

Message Queue

Asynchronous Communications Protocol
Data Error Reduction
Message Encryption
On-Premise Installation
Roles / Permissions
Storage / Retrieval / Deletion
System Decoupling

Product Features

Message Queue

Asynchronous Communications Protocol
Data Error Reduction
Message Encryption
On-Premise Installation
Roles / Permissions
Storage / Retrieval / Deletion
System Decoupling

Alternatives

Alternatives

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