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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 Apache Kafka?

Apache Kafka® is a powerful, open-source solution tailored for distributed streaming applications. It supports the expansion of production clusters to include up to a thousand brokers, enabling the management of trillions of messages each day and overseeing petabytes of data spread over hundreds of thousands of partitions. The architecture offers the capability to effortlessly scale storage and processing resources according to demand. Clusters can be extended across multiple availability zones or interconnected across various geographical locations, ensuring resilience and flexibility. Users can manipulate streams of events through diverse operations such as joins, aggregations, filters, and transformations, all while benefiting from event-time and exactly-once processing assurances. Kafka also includes a Connect interface that facilitates seamless integration with a wide array of event sources and sinks, including but not limited to Postgres, JMS, Elasticsearch, and AWS S3. Furthermore, it allows for the reading, writing, and processing of event streams using numerous programming languages, catering to a broad spectrum of development requirements. This adaptability, combined with its scalability, solidifies Kafka's position as a premier choice for organizations aiming to leverage real-time data streams efficiently. With its extensive ecosystem and community support, Kafka continues to evolve, addressing the needs of modern data-driven enterprises.

Media

Media

Integrations Supported

5X
Cognee
CorralData
Databricks Data Intelligence Platform
Dataplane
Deep.BI
Edge Delta
FusionAuth
Hackolade
Ikigai
InsightFinder
Kapacitor
LeanXcale
MayaData
QEDIT
Selector Analytics
Sprinkle
Theom
Upstash
kPow

Integrations Supported

5X
Cognee
CorralData
Databricks Data Intelligence Platform
Dataplane
Deep.BI
Edge Delta
FusionAuth
Hackolade
Ikigai
InsightFinder
Kapacitor
LeanXcale
MayaData
QEDIT
Selector Analytics
Sprinkle
Theom
Upstash
kPow

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

The Apache Software Foundation

Date Founded

1999

Company Location

United States

Company Website

kafka.apache.org

Categories and Features

iPaaS

AI / Machine Learning
Cloud Data Integration
Dashboard
Data Quality Control
Data Security
Drag & Drop
Embedded iPaaS
Integration Management
Pre-Built Connectors
White Label
Workflow Management

Message Queue

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

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