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Description

AWS Batch provides a streamlined platform for developers, scientists, and engineers to efficiently execute vast numbers of batch computing jobs on the AWS cloud infrastructure. It automatically allocates the ideal quantity and types of compute resources, such as CPU or memory-optimized instances, tailored to the demands and specifications of the submitted batch jobs. By utilizing AWS Batch, users are spared from the hassle of installing and managing batch computing software or server clusters, enabling them to concentrate on result analysis and problem-solving. The service organizes, schedules, and manages batch workloads across a comprehensive suite of AWS compute offerings, including AWS Fargate, Amazon EC2, and Spot Instances. Importantly, there are no extra fees associated with AWS Batch itself; users only incur costs for the AWS resources, such as EC2 instances or Fargate jobs, that they deploy for executing and storing their batch jobs. This makes AWS Batch not only efficient but also cost-effective for handling large-scale computing tasks. As a result, organizations can optimize their workflows and improve productivity without being burdened by complex infrastructure management.

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

AWS Fargate
AWS EC2 Trn3 Instances
AWS ParallelCluster
AWS Step Functions
Amazon FSx for Lustre
Amazon Fresh
Amazon Kinesis
Amazon Linux 2
Apache Avro
Apache Kafka
BMC AMI Ops Automation for Capping
Flyte
Kubernetes
Python
RadiantOne
Redis
Rust
SQL
Stonebranch
Union Cloud

Integrations

AWS Fargate
AWS EC2 Trn3 Instances
AWS ParallelCluster
AWS Step Functions
Amazon FSx for Lustre
Amazon Fresh
Amazon Kinesis
Amazon Linux 2
Apache Avro
Apache Kafka
BMC AMI Ops Automation for Capping
Flyte
Kubernetes
Python
RadiantOne
Redis
Rust
SQL
Stonebranch
Union Cloud

Pricing Details

No price information available.
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/batch/

Vendor Details

Company Name

Arroyo

Country

United States

Website

www.arroyo.dev/

Product Features

DevOps

Approval Workflow
Dashboard
KPIs
Policy Management
Portfolio Management
Prioritization
Release Management
Timeline Management
Troubleshooting Reports

Alternatives

Azure Batch Reviews

Azure Batch

Microsoft

Alternatives

AWS Fargate Reviews

AWS Fargate

Amazon