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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 Data Taps?

Build your data pipelines like putting together Lego pieces with Data Taps, enabling you to integrate new metric layers and explore thoroughly while utilizing real-time streaming SQL for inquiries. Work alongside your colleagues to share and access data globally, making enhancements and adjustments to your system with ease. Adapt your setup to include diverse models and schemas while evolving your architecture as needed. Engineered for scalability, it harnesses the capabilities of AWS Lambda and S3 to ensure high performance. This adaptability empowers teams to respond swiftly to the dynamic requirements of data. Ultimately, this approach fosters innovation and collaboration in data management.

Media

Media

No images available

Integrations Supported

AWS Lambda
Amazon S3
Apache Tomcat
Cloud Foundry
Kubernetes
Spring
Spring Framework
VMware Cloud

Integrations Supported

AWS Lambda
Amazon S3
Apache Tomcat
Cloud Foundry
Kubernetes
Spring
Spring Framework
VMware Cloud

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
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

Data Taps

Date Founded

2023

Company Location

Finland

Company Website

www.taps.boilingdata.com

Categories and Features

Big Data

Collaboration
Data Blends
Data Cleansing
Data Mining
Data Visualization
Data Warehousing
High Volume Processing
No-Code Sandbox
Predictive Analytics
Templates

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