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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

Description

Effortlessly capture, modify, and transfer streaming data in real time. You can create a delivery stream, choose your desired destination, and begin streaming data with minimal effort. The system automatically provisions and scales necessary compute, memory, and network resources without the need for continuous management. You can convert raw streaming data into various formats such as Apache Parquet and dynamically partition it without the hassle of developing your processing pipelines. Amazon Data Firehose is the most straightforward method to obtain, transform, and dispatch data streams in mere seconds to data lakes, data warehouses, and analytics platforms. To utilize Amazon Data Firehose, simply establish a stream by specifying the source, destination, and any transformations needed. The service continuously processes your data stream, automatically adjusts its scale according to the data volume, and ensures delivery within seconds. You can either choose a source for your data stream or utilize the Firehose Direct PUT API to write data directly. This streamlined approach allows for greater efficiency and flexibility in handling data streams.

Description

Scale from zero to millions of events per second effortlessly. Arroyo is delivered as a single, compact binary, allowing for local development on MacOS or Linux, and seamless deployment to production environments using Docker or Kubernetes. As a pioneering stream processing engine, Arroyo has been specifically designed to simplify real-time processing, making it more accessible than traditional batch processing. Its architecture empowers anyone with SQL knowledge to create dependable, efficient, and accurate streaming pipelines. Data scientists and engineers can independently develop comprehensive real-time applications, models, and dashboards without needing a specialized team of streaming professionals. By employing SQL, users can transform, filter, aggregate, and join data streams, all while achieving sub-second response times. Your streaming pipelines should remain stable and not trigger alerts simply because Kubernetes has chosen to reschedule your pods. Built for modern, elastic cloud infrastructures, Arroyo supports everything from straightforward container runtimes like Fargate to complex, distributed setups on Kubernetes, ensuring versatility and robust performance across various environments. This innovative approach to stream processing significantly enhances the ability to manage data flows in real-time applications.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Amazon Kinesis
Apache Parquet
AWS Network Firewall
Amazon CloudWatch
Amazon MSK
Amazon OpenSearch Service
Amazon Redshift
Amazon Simple Notification Service (SNS)
Amazon Web Services (AWS)
Apache Avro
Apache Flink
Apache Iceberg
Apache Kafka
Confluent
JSON
Orchestra
PostgreSQL
Python
Rust
Snowflake

Integrations

Amazon Kinesis
Apache Parquet
AWS Network Firewall
Amazon CloudWatch
Amazon MSK
Amazon OpenSearch Service
Amazon Redshift
Amazon Simple Notification Service (SNS)
Amazon Web Services (AWS)
Apache Avro
Apache Flink
Apache Iceberg
Apache Kafka
Confluent
JSON
Orchestra
PostgreSQL
Python
Rust
Snowflake

Pricing Details

$0.075 per month
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Amazon

Founded

1994

Country

United States

Website

aws.amazon.com/firehose/

Vendor Details

Company Name

Arroyo

Country

United States

Website

www.arroyo.dev/

Product Features

Alternatives

Alternatives

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