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What is Spring Cloud Data Flow?

The architecture based on microservices fosters effective handling of both streaming and batch data processing, particularly suited for environments such as Cloud Foundry and Kubernetes. By implementing Spring Cloud Data Flow, users are empowered to craft complex topologies for their data pipelines, utilizing Spring Boot applications built with the frameworks of Spring Cloud Stream or Spring Cloud Task. This robust platform addresses a wide array of data processing requirements, including ETL, data import/export, event streaming, and predictive analytics. The server component of Spring Cloud Data Flow employs Spring Cloud Deployer, which streamlines the deployment of data pipelines comprising Spring Cloud Stream or Spring Cloud Task applications onto modern infrastructures like Cloud Foundry and Kubernetes. Moreover, a thoughtfully curated collection of pre-configured starter applications for both streaming and batch processing enhances various data integration and processing needs, assisting users in their exploration and practical applications. In addition to these features, developers are given the ability to develop bespoke stream and task applications that cater to specific middleware or data services, maintaining alignment with the accessible Spring Boot programming model. This level of customization and flexibility ultimately positions Spring Cloud Data Flow as a crucial resource for organizations aiming to refine and enhance their data management workflows. Overall, its comprehensive capabilities facilitate a seamless integration of data processing tasks into everyday operations.

What is Amazon MSK?

Amazon Managed Streaming for Apache Kafka (Amazon MSK) streamlines the creation and management of applications that utilize Apache Kafka for processing streaming data. As an open-source solution, Apache Kafka supports the development of real-time data pipelines and applications. By employing Amazon MSK, you can take advantage of Apache Kafka’s native APIs for a range of functions, including filling data lakes, enabling data interchange between databases, and supporting machine learning and analytical initiatives. Nevertheless, independently managing Apache Kafka clusters can be quite challenging, as it involves tasks such as server provisioning, manual setup, and addressing server outages. Furthermore, it requires you to manage updates and patches, design clusters for high availability, securely and durably store data, set up monitoring systems, and strategically plan for scaling to handle varying workloads. With Amazon MSK, many of these complexities are mitigated, allowing you to concentrate more on application development rather than the intricacies of infrastructure management. This results in enhanced productivity and more efficient use of resources in your projects.

Media

Media

Integrations Supported

5X
Amazon Data Firehose
Amazon EC2
Apache Kafka
Apache Tomcat
Argonaut
Cloud Foundry
Datadog
Kubernetes
Lenses
New Relic
Onehouse
Protegrity
Spring
Spring Framework
Sumo Logic
Tenzir
VMware Cloud
Waterstream
kPow

Integrations Supported

5X
Amazon Data Firehose
Amazon EC2
Apache Kafka
Apache Tomcat
Argonaut
Cloud Foundry
Datadog
Kubernetes
Lenses
New Relic
Onehouse
Protegrity
Spring
Spring Framework
Sumo Logic
Tenzir
VMware Cloud
Waterstream
kPow

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

$0.0543 per hour
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Spring

Company Website

spring.io/projects/spring-cloud-dataflow

Company Facts

Organization Name

Amazon

Date Founded

1994

Company Location

United States

Company Website

aws.amazon.com/msk/

Categories and Features

Streaming Analytics

Data Enrichment
Data Wrangling / Data Prep
Multiple Data Source Support
Process Automation
Real-time Analysis / Reporting
Visualization Dashboards

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