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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.

What is Amazon Data Firehose?

Easily capture, transform, and load live streaming data with minimal effort through straightforward steps. Begin by setting up a delivery stream, choosing your preferred destination, and you’ll be ready to stream data in real-time almost instantly. The system intelligently provisions and modifies compute, memory, and network resources without requiring constant oversight. You can convert raw streaming data into various formats like Apache Parquet while seamlessly partitioning the data in real-time, all without the need to develop your own processing frameworks. Amazon Data Firehose is recognized as the easiest option for quickly acquiring, transforming, and delivering data streams to data lakes, warehouses, and analytical platforms. To start using Amazon Data Firehose, you must create a stream that comprises a source, destination, and any required transformations. The service continuously oversees the data stream, automatically adjusting to fluctuations in data volume and ensuring almost instantaneous delivery. You have the flexibility to select a source for your data stream or take advantage of the Firehose Direct PUT API for direct data input. This efficient approach not only simplifies the process but also enhances performance when managing large data volumes, making it an invaluable tool for any data-driven operation. Furthermore, its ability to handle various data types ensures that users can adapt to diverse analytics needs.

Media

Media

Integrations Supported

Apache Parquet
Amazon S3
Apache Avro
Azure Blob Storage
Google Cloud Storage
Google Sheets
JSON
Python
Rust
SDF

Integrations Supported

Apache Parquet
AWS Network Firewall
Amazon CloudWatch
Amazon MSK
Amazon OpenSearch Service
Amazon Redshift
Amazon Web Services (AWS)
Apache Iceberg
Doctor Droid
Orchestra
Snowflake

API Availability

Has API

API Availability

Has API

Pricing Information

Free
Free Version

Pricing Information

$0.075 per month
Free Trial Offered?

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
On-Site Training

Training Options

Documentation Hub
Webinars
On-Site Training

Company Facts

Organization Name

Apache Software Foundation

Date Founded

2019

Company Location

United States

Company Website

datafusion.apache.org

Company Facts

Organization Name

Amazon

Date Founded

1994

Company Location

United States

Company Website

aws.amazon.com/firehose/

Categories and Features

Database

Not specified

Categories and Features

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