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What is Google Cloud Data Fusion?

Open core technology enables the seamless integration of hybrid and multi-cloud ecosystems. Based on the open-source project CDAP, Data Fusion ensures that users can easily transport their data pipelines wherever needed. The broad compatibility of CDAP with both on-premises solutions and public cloud platforms allows users of Cloud Data Fusion to break down data silos and tap into valuable insights that were previously inaccessible. Furthermore, its effortless compatibility with Google’s premier big data tools significantly enhances user satisfaction. By utilizing Google Cloud, Data Fusion not only bolsters data security but also guarantees that data is instantly available for comprehensive analysis. Whether you are building a data lake with Cloud Storage and Dataproc, loading data into BigQuery for extensive warehousing, or preparing data for a relational database like Cloud Spanner, the integration capabilities of Cloud Data Fusion enable fast and effective development while supporting rapid iterations. This all-encompassing strategy ultimately empowers organizations to unlock greater potential from their data resources, fostering innovation and informed decision-making. In an increasingly data-driven world, leveraging such technologies is crucial for maintaining a competitive edge.

What is Google Cloud Dataflow?

A data processing solution that combines both streaming and batch functionalities in a serverless, cost-effective manner is now available. This service provides comprehensive management for data operations, facilitating smooth automation in the setup and management of necessary resources. With the ability to scale horizontally, the system can adapt worker resources in real time, boosting overall efficiency. The advancement of this technology is largely supported by the contributions of the open-source community, especially through the Apache Beam SDK, which ensures reliable processing with exactly-once guarantees. Dataflow significantly speeds up the creation of streaming data pipelines, greatly decreasing latency associated with data handling. By embracing a serverless architecture, development teams can concentrate more on coding rather than navigating the complexities involved in server cluster management, which alleviates the typical operational challenges faced in data engineering. This automatic resource management not only helps in reducing latency but also enhances resource utilization, allowing teams to maximize their operational effectiveness. In addition, the framework fosters an environment conducive to collaboration, empowering developers to create powerful applications while remaining free from the distractions of managing the underlying infrastructure. As a result, teams can achieve higher productivity and innovation in their data processing initiatives.

Media

Media

Integrations Supported

Google Cloud Datastream
Google Cloud Platform
Pantomath
CData Connect
DataBuck
Dropbox Dash
Google Cloud BigQuery
Google Cloud Bigtable
Google Cloud Composer
Google Cloud Dataplex
Google Cloud IoT Core
Google Cloud Profiler
IntelliPay
New Relic
Orchestra
Protegrity
Sedai
Telmai
Ternary

Integrations Supported

Google Cloud Datastream
Google Cloud Platform
Pantomath
CData Connect
DataBuck
Dropbox Dash
Google Cloud BigQuery
Google Cloud Bigtable
Google Cloud Composer
Google Cloud Dataplex
Google Cloud IoT Core
Google Cloud Profiler
IntelliPay
New Relic
Orchestra
Protegrity
Sedai
Telmai
Ternary

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

Google

Company Location

United States

Company Website

cloud.google.com/data-fusion

Company Facts

Organization Name

Google

Date Founded

1998

Company Location

United States

Company Website

cloud.google.com/dataflow

Categories and Features

ETL

Data Analysis
Data Filtering
Data Quality Control
Job Scheduling
Match & Merge
Metadata Management
Non-Relational Transformations
Version Control

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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