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Description
SiteWhere utilizes Kubernetes for deploying its infrastructure and microservices, making it versatile for both on-premise setups and virtually any cloud service provider. The system is supported by robust configurations of Apache Kafka, Zookeeper, and Hashicorp Consul, ensuring a reliable infrastructure. Each microservice is designed to scale individually while also enabling seamless integration with others. It presents a comprehensive multitenant IoT ecosystem that encompasses device management, event ingestion, extensive event storage capabilities, REST APIs, data integration, and additional features. The architecture is distributed and developed using Java microservices that operate on Docker, with an Apache Kafka processing pipeline for efficiency. Importantly, SiteWhere CE remains open source, allowing free use for both personal and commercial purposes. Additionally, the SiteWhere team provides free basic support along with a continuous flow of innovative features to enhance the platform's functionality. This emphasis on community-driven development ensures that users can benefit from ongoing improvements and updates.
Description
Microservices architecture enables efficient streaming and batch data processing specifically designed for platforms like Cloud Foundry and Kubernetes. By utilizing Spring Cloud Data Flow, users can effectively design intricate topologies for their data pipelines, which feature Spring Boot applications developed with the Spring Cloud Stream or Spring Cloud Task frameworks. This powerful tool caters to a variety of data processing needs, encompassing areas such as ETL, data import/export, event streaming, and predictive analytics. The Spring Cloud Data Flow server leverages Spring Cloud Deployer to facilitate the deployment of these data pipelines, which consist of Spring Cloud Stream or Spring Cloud Task applications, onto contemporary infrastructures like Cloud Foundry and Kubernetes. Additionally, a curated selection of pre-built starter applications for streaming and batch tasks supports diverse data integration and processing scenarios, aiding users in their learning and experimentation endeavors. Furthermore, developers have the flexibility to create custom stream and task applications tailored to specific middleware or data services, all while adhering to the user-friendly Spring Boot programming model. This adaptability makes Spring Cloud Data Flow a valuable asset for organizations looking to optimize their data workflows.
API Access
Has API
API Access
Has API
Integrations
Kubernetes
Amazon Web Services (AWS)
Apache Kafka
Apache Tomcat
Apache ZooKeeper
Cloud Foundry
Google Cloud Platform
HashiCorp Consul
Helm
Mariner Financial Wellness
Integrations
Kubernetes
Amazon Web Services (AWS)
Apache Kafka
Apache Tomcat
Apache ZooKeeper
Cloud Foundry
Google Cloud Platform
HashiCorp Consul
Helm
Mariner Financial Wellness
Pricing Details
No price information available.
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
SiteWhere
Website
sitewhere.io
Vendor Details
Company Name
Spring
Website
spring.io/projects/spring-cloud-dataflow