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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 Apache DataFusion?

Apache DataFusion is a highly adaptable and capable query engine developed in Rust, which utilizes Apache Arrow for efficient in-memory data handling. It is intended for developers who are working on data-centric systems, including databases, data frames, machine learning applications, and real-time data streaming solutions. Featuring both SQL and DataFrame APIs, DataFusion offers a vectorized, multi-threaded execution engine that efficiently manages data streams while accommodating a variety of partitioned data sources. It supports numerous native file formats, including CSV, Parquet, JSON, and Avro, and integrates seamlessly with popular object storage services such as AWS S3, Azure Blob Storage, and Google Cloud Storage. The architecture is equipped with a sophisticated query planner and an advanced optimizer, which includes features like expression coercion, simplification, and distribution-aware optimizations, as well as automatic join reordering for enhanced performance. Additionally, DataFusion provides significant customization options, allowing developers to implement user-defined scalar, aggregate, and window functions, as well as integrate custom data sources and query languages, thereby enhancing its utility for a wide range of data processing scenarios. This flexibility ensures that developers can effectively adjust the engine to meet their specific requirements and optimize their data workflows.

Media

Media

Integrations Supported

Dropbox Dash
Google Cloud BigQuery
Google Cloud Datastream
Google Cloud Platform
IntelliPay
Pantomath

Integrations Supported

Amazon S3
Apache Arrow
Apache Avro
Apache Parquet
Azure Blob Storage
C
Google Cloud Storage
Google Sheets
JSON
Microsoft Excel
Python
Rust
SDF
SQL

API Availability

API Availability

Has API

Pricing Information

Pricing not provided
Free Trial Offered?

Pricing Information

Free
Free Version

Supported Platforms

SaaS
On-Prem

Supported Platforms

SaaS

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub
On-Site Training

Company Facts

Organization Name

Google

Company Location

United States

Company Website

cloud.google.com/data-fusion

Company Facts

Organization Name

Apache Software Foundation

Date Founded

2019

Company Location

United States

Company Website

datafusion.apache.org

Categories and Features

Data Integration

Not specified

Data Pipeline

Not specified

ETL

Data Analysis
Data Filtering
Data Quality Control
Job Scheduling
Match & Merge
Metadata Management
Version Control

Categories and Features

Database

Not specified

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